Automate Your Data Engineering Jobs Search: Using ChatGPT, RSS & Alerts to Save Hours Each Week
Data roles drop across banks, scaleups, consultancies, public sector & product teams daily—often hidden in ATS portals or duplicated across boards. The fix: put discovery on rails with keyword-rich alerts, RSS feeds & a reusable ChatGPT workflow that triages listings, ranks fit, & tailors your CV in minutes.
This copy-paste playbook is for www.dataengineeringjobs.co.uk readers. It’s UK-centric, practical, & designed to save you hours every week.
What You’ll Have Working In 30 Minutes
A role & keyword map across Data Engineering, Platform, Streaming, Analytics Engineering, DataOps, Governance & MLOps-adjacent work.
Shareable Boolean strings for Google & job boards that strip out noise.
Always-on alerts & RSS feeds that bring fresh UK roles to you.
A ChatGPT “Data Job Scout” prompt that deduplicates, scores match & outputs ready-to-paste actions.
A simple pipeline tracker so deadlines & follow-ups never slip.
Step 1: Define Role Clusters & Your Keyword Map
Titles vary by employer. Build clusters so your searches catch synonyms & adjacent roles.
Core Data Engineering
Titles: Data Engineer, Senior Data Engineer, ETL/ELT Engineer, Data Platform Engineer.
Keywords: SQL, Python, Spark/PySpark, dbt, Airflow/Prefect/Dagster, CI/CD, Git.
Lakehouse, Warehouses & Storage
Tech: Databricks (Delta/DLT), Snowflake (Tasks/Streams/Snowpipe), BigQuery, Redshift, Synapse, Delta Lake, Apache Iceberg, Apache Hudi.
Cloud storage: S3, ADLS, GCS. Table formats, partitioning, Z-Ordering, clustering.
Streaming & Real-Time
Titles: Streaming Engineer, Real-Time Data Engineer, Data Streaming Platform.
Tech: Kafka/Kafka Connect/KSQL, Flink, Spark Structured Streaming, Pub/Sub, Kinesis, Event Hubs, Debezium (CDC).
Analytics Engineering
Titles: Analytics Engineer, BI Data Engineer.
Tech: dbt, SQL modelling, tests, macros, version control; BI: Looker, Power BI, Tableau; metrics layers, semantic models.
DataOps, Quality & Observability
Tools: Great Expectations, Soda, dbt tests, Monte Carlo, Datafold; lineage/catalogue (DataHub, OpenLineage, Collibra, Alation), SLAs, freshness.
Infra: Terraform/Pulumi, Docker/Kubernetes, GitHub Actions/GitLab CI, Airflow ops.
MLOps-adjacent
Titles: ML Data Engineer, Feature Engineer, ML Platform Engineer.
Tech: feature stores, model registry, MLflow, Feast, Databricks Feature Store.
Governance & Security
Terms: GDPR, PII, data masking, row-level security, IAM, KMS/Key Vault/Cloud KMS, encryption at rest/in transit, DLP.
UK Locations & Modes
London, Manchester, Bristol, Cambridge, Oxford, Edinburgh, Glasgow, Leeds, Birmingham, Newcastle, Reading, Belfast.
Modes: Remote UK, Hybrid, On-site (regulated work may need on-site/clearance).
Modifiers: “Visa sponsorship”, “Skilled Worker visa”, “Security clearance”, “Graduate”, “Internship”, “Permanent”.
Capture this in a notes file—your keyword map fuels alerts, feeds & prompts.
Step 2: Build Precise Boolean Searches (Copy & Paste)
Use these in Google & on job boards. Start broad, then refine with site: filters where signal lives.
General UK Data Engineering Search
("Data Engineer" OR "Data Platform Engineer" OR "Analytics Engineer" OR "Streaming Engineer")
(Snowflake OR BigQuery OR Redshift OR Databricks OR "Delta Lake" OR dbt OR Airflow OR Kafka OR Spark)
(UK OR "United Kingdom" OR London OR Manchester OR Bristol OR Edinburgh OR Cambridge OR Leeds)
("Permanent" OR "Full-time") -site:indeed.co.uk -site:glassdoor.co.uk
Warehouses/Lakehouse (dbt + cloud)
("Data Engineer" OR "Analytics Engineer")
(dbt OR "semantic layer" OR "metrics layer") (Snowflake OR BigQuery OR Redshift OR Databricks)
(UK OR "Remote UK")
Streaming & CDC
("Streaming Engineer" OR "Real-time" OR "Data Streaming" OR "Stream Processing")
(Kafka OR "Kafka Connect" OR Debezium OR Flink OR "Structured Streaming" OR Kinesis OR "Event Hubs" OR Pub/Sub)
(UK OR "Remote UK")
Databricks/Spark-heavy
("Data Engineer" OR "Data Platform") (Databricks OR PySpark OR "Delta Live Tables" OR MLflow)
(S3 OR ADLS OR GCS) (UK OR "Remote UK")
Snowflake-heavy
("Data Engineer" OR "Analytics Engineer") (Snowflake OR "Snowpipe" OR "Streams" OR "Tasks") (dbt OR Airflow)
(UK OR "Remote UK")
DataOps/Observability
("DataOps" OR "Data Quality" OR "Data Observability" OR "Data Reliability")
("Great Expectations" OR Soda OR "Monte Carlo" OR "Datafold" OR "OpenLineage" OR DataHub)
(UK OR "Remote UK")
Governance/Security
("Data Governance" OR "Data Steward" OR "Data Security" OR "Data Privacy")
(GDPR OR "row-level security" OR masking OR "PII" OR IAM OR "Key Vault" OR KMS)
(UK OR "Remote UK")
Graduate & Early Career
("Graduate" OR "Junior" OR "Internship") ("data engineer" OR "analytics engineer" OR "ETL") (SQL OR Python) (UK OR "Remote UK")
Visa/clearance (optional)
("Data Engineer" OR "Analytics Engineer") ("visa sponsorship" OR "Skilled Worker visa" OR "security clearance") (UK)
ATS & Employer Career Sites (cuts aggregator noise)
("Data Engineer" OR "Analytics Engineer" OR "Data Platform" OR "Streaming Engineer")
(site:boards.greenhouse.io OR site:lever.co OR site:workable.com OR site:ashbyhq.com OR site:smartrecruiters.com OR site:icims.com OR site:successfactors.com)
(UK OR "Remote UK")
Step 3: Turn Searches Into Google Alerts & RSS
Let fresh postings come to you.
Setup (quick):
Open Google Alerts.
Paste a Boolean string.
Show options → choose At most once a day (daily is ideal) or As-it-happens if you’re sprinting.
Deliver to: select RSS feed (paste into Feedly/Inoreader) or email.
Create separate alerts per cluster: Warehouse/Lakehouse, Streaming, Databricks/Spark, Snowflake, DataOps/Observability, Governance/Security, Graduate.
Good alert examples (copy-paste):
("Data Engineer" OR "Analytics Engineer") (dbt OR "semantic layer") (Snowflake OR BigQuery OR Redshift OR Databricks) (UK OR "Remote UK")
("Streaming Engineer" OR "Real-time") (Kafka OR Flink OR "Structured Streaming" OR Debezium OR Kinesis OR Pub/Sub OR "Event Hubs") (UK OR "Remote UK")
("Data Engineer" OR "Data Platform") (Databricks OR PySpark OR "Delta Live Tables" OR MLflow) (S3 OR ADLS OR GCS) (UK OR "Remote UK")
("DataOps" OR "Data Quality" OR "Data Observability") ("Great Expectations" OR Soda OR "Monte Carlo" OR Datafold OR DataHub) (UK OR "Remote UK")
Pro tips
Keep one alert per intent to preserve relevance.
Pair locations sensibly: London + “Remote UK” catches most UK-based roles.
Use
-site:to mute noisy domains that overwhelm your feed.
Prefer RSS? Tag/star items & export starred roles as CSV—ideal for a weekly planning pass in ChatGPT.
Step 4: Use ChatGPT as Your “Data Job Scout”
Alerts & RSS deliver raw listings. ChatGPT turns them into a shortlist with actions so you apply faster & better.
Reusable system prompt (edit to your targets):
System role: You are my Data Job Scout for UK roles. Parse pasted job listings (title, company, location, link, snippet), remove duplicates by company+title+location, and produce a ranked shortlist to my criteria. Then provide tailored actions for each role.
My criteria:
• Target clusters: Warehouse/Lakehouse (dbt + Snowflake/BigQuery/Redshift/Databricks), Streaming (Kafka/Flink/Spark), DataOps/Observability, Governance/Security.
• Must-haves by cluster:
- Warehouse/Lakehouse: SQL, dbt, ELT, dimensional/medallion modelling, CI/CD.
- Streaming: Kafka/Connect/Debezium, Flink/Spark Streaming, exactly-once, backpressure handling.
- Databricks/Spark: PySpark, Delta Lake/DLT, optimisation (file sizes, partitions), job orchestration.
- Snowflake: tasks/streams/snowpipe, performance tuning (clustering, micro-partitions), RBAC.
- DataOps: Great Expectations/Soda, lineage, SLAs, Airflow/Prefect/Dagster, Terraform.
- Governance/Security: GDPR/PII, RLS/masking, IAM/KMS, catalogues.
• Location: Remote UK or London/Manchester/Cambridge/Bristol hybrid.
• Salary: £XX–£YY (flex if exceptional).
• Exclude: pure BI developer roles, contract <3 months, agency spam.
Output:
1) Summary: counts & duplicates removed; scoring logic (2 lines).
2) Ranked Shortlist (max 10): Title — Company — Location — Link — Score (0–100) — 1–2 line fit rationale.
3) Per-role actions:
- 3 tailored CV bullets (impact-led, tools & outcomes).
- 6–10 keywords to mirror (stack/patterns/SLAs).
- A 3-sentence message to the hiring contact referencing one concrete requirement.
4) Today plan: order to apply with time estimates.
Daily run (paste your feed)
Here are today’s roles (Title — Company — Location — Link — Snippet):
1) ...
2) ...
Apply the Data Job Scout system prompt.
Deep-dive on a single role (for the perfect match)
Analyse this spec for must-haves, repeated terms & implied priorities. Then:
• Write 3 CV bullets that mirror the spec (warehouse/lakehouse/streaming/dataops/governance), each ending with a measurable outcome.
• Draft a 120-word cover note referencing the stack & one 30-day quick win.
• List 10 keywords/phrases to include naturally (services, patterns, metrics).
• Provide 6 likely interview questions with succinct model answers using my background.
Job spec: [paste]
My background: [4–8 bullets with stack & outcomes]
Fast CV tailoring prompts (cluster-specific)
Warehouse/Lakehouse (dbt + cloud)
Create 5 “Recent Impact” bullets showing dbt modelling/tests, ELT to Snowflake/BigQuery/Redshift, CI/CD & cost/perf tuning—one line each with metrics.
Spec: [paste]
Databricks/Spark
Produce 5 bullets covering PySpark optimisation, Delta Lake design, DLT pipelines & job orchestration—each with runtime/cost improvements.
Spec: [paste]
Streaming
Write 5 bullets on Kafka/Connect/Debezium CDC, Flink/Spark Streaming, backpressure, exactly-once semantics & SLAs—each with latency/throughput metrics.
Spec: [paste]
DataOps/Observability
Draft 5 bullets highlighting Great Expectations/Soda, freshness/lineage SLAs, Airflow/Dagster reliability & incident reduction—each with measurable outcomes.
Spec: [paste]
Governance/Security
Output 5 bullets on GDPR/PII handling, RLS/masking, IAM/KMS, audit trails & catalogues—each with compliance or risk reduction metrics.
Spec: [paste]
Step 5: Optional No-Code Automation (Email, Slack, Notion)
Email filters: Route alert emails into a “Data-Jobs” label. Each morning, paste the best items into ChatGPT & run your Job Scout prompt.
RSS rules: Tag feeds by cluster (Warehouse/Lakehouse, Streaming, Databricks/Spark, Snowflake, DataOps, Governance). Star the best & export as CSV for a weekly planning pass.
Notion/Sheets: Keep one tracker & paste it into ChatGPT for daily prioritisation & follow-up drafting.
Slack/Discord: Post starred roles via webhook into a private channel for faster triage.
Step 6: A Simple Pipeline Tracker That Wins Interviews
Suggested columns
Date found
Role
Company
Location
Link
Cluster (Warehouse/Lakehouse/Streaming/Databricks/Snowflake/DataOps/Governance)
Match score (0–100)
Status (To apply / Applied / Interview / Offer / On hold / Rejected)
Deadline / due date
Contact (name, LinkedIn/email)
Notes (stack, patterns, metrics)
Next action (what & when)
Follow-up rhythm
T+3 days: polite nudge if no acknowledgement.
T+10 days: request an update; include a small proof point (e.g., a redacted optimisation note—no confidential data).
Post-interview: thank-you within 24 hours; reference one spec requirement & a 30-day quick win.
Shareable Prompt Library (Data-Specific)
1) Role Decoder
Explain this data engineering role in plain English: first 90-day deliverables, 3 hardest problems & the exact skills they truly need (stack, patterns, SLAs). Then list the top 12 CV keywords they’ll search for. [paste spec]
2) Company Fit Snapshot
From the spec & site notes, infer warehouse/lakehouse choice, orchestration, governance posture & priorities (cost, reliability, time-to-data). Output a 6-bullet “Why me, why now” pitch.
[spec + brief company notes]
3) CV Bullet Rewriter (Impact-led)
Rewrite these bullets with action+tool+metric, mirroring the spec vocabulary (dbt models/tests, Spark/Delta, Snowflake Tasks/Streams, Kafka/Flink, SLAs). One line each, UK spelling.
[bullets + spec]
4) Outreach Message (120 words)
Draft a concise message for the hiring contact that references one stack detail (e.g., dbt+Snowflake or Databricks DLT) & proposes a 30-day quick win. Mirror 3 spec keywords. Confident tone, no fluff.
[spec + company notes]
5) Interview Pack Generator
Produce 8 technical questions + short model answers tailored to this spec (warehouse/lakehouse/streaming/dataops/governance), plus 5 behavioural questions with STAR hints using my background.
[spec + background]
6) Offer & Salary Prep (UK)
Given the role, my years of experience & market norms, suggest a negotiation range in GBP, non-salary levers (training budget, certifications, conferences, on-call), & 3 crisp value statements I can use.
[spec + experience]
Keyword & Query Bank (Use Across Alerts, Feeds & Boards)
Titles
Data Engineer, Senior Data Engineer, Data Platform Engineer, Streaming Engineer, Analytics Engineer, ML Data Engineer, DataOps Engineer, Data Governance Specialist, Data Architect.
Warehouses/Lakehouse
Snowflake (Tasks/Streams/Snowpipe, RBAC, clustering), BigQuery (slots/cost controls/partitions), Redshift (RA3/sort & dist keys), Databricks (Delta/DLT/Unity Catalog), Synapse, Lake Formation.
Pipelines & Orchestration
dbt, Airflow, Dagster, Prefect, Kafka Connect, Debezium, CDC, Fivetran, Airbyte.
Processing
Spark/PySpark, Flink, SQL (window functions/CTEs), UDFs, partitioning, Z-Order, broadcast joins, AQE.
Cloud & Infra
AWS (S3, Glue, EMR, Lambda, Kinesis), Azure (ADLS, Synapse, ADF, Event Hubs), GCP (GCS, Dataflow, Dataproc, Pub/Sub, Composer), Terraform, Docker, Kubernetes, CI/CD.
DataOps/Observability
Great Expectations, Soda, Monte Carlo, Datafold, OpenLineage, DataHub, Amundsen, lineage, freshness, SLAs.
Governance & Security
GDPR, PII, DLP, RLS, masking, encryption, IAM, KMS/Key Vault/Cloud KMS, audit, catalogues.
BI & Metrics
Looker, Power BI, Tableau, semantic/metrics layers, dbt exposures.
Modifiers
Remote UK, Hybrid, On-site, Permanent, Contract, Graduate, Internship, Visa sponsorship, Security clearance.
Sample Daily Workflow (7–12 Minutes)
Open your alert folder/RSS. Skim titles; bin obvious mismatches.
Paste 10–30 items into ChatGPT with your Data Job Scout prompt.
Review the shortlist. Open the top 3–5 high-score roles.
Run the deep-dive prompt on your favourite; generate tailored CV bullets & a 120-word cover note.
Update your tracker & set deadlines.
Apply in one sitting—mirror 6–10 keywords naturally (stack, patterns, SLAs).
Schedule follow-ups right away.
Consistency beats weekend blitzes.
Troubleshooting & Tuning
“Still getting noise.”
Tighten with stack tokens (dbt, Delta Lake, Kafka, Flink) & exclude agency spam via -site: or -"recruitment agency".
“All senior roles.”
Include (Junior OR Mid OR "2-4 years") & exclude (Senior OR Principal OR Lead).
“Remote isn’t really UK-based.”
Use ("Remote UK" OR "UK-based remote" OR "right to work in the UK") & exclude "anywhere" if needed.
“I want regulated/secure environments.”
Add GDPR, PII, security clearance, ISO 27001, sector tags (Public Sector, Defence, FS, Healthcare).
“I want real-time only.”
Bias searches to Flink, Kafka, Debezium, exactly-once, low-latency, & exclude batch if it clutters results.
Lightweight Tracker Template (Copy Text)
Date Found | Role | Company | Location | Link | Cluster | Match (0–100) | Status | Deadline | Contact | Notes | Next Action
Status: To apply / Applied / Interview / Offer / On hold / Rejected
Daily command for ChatGPT:
“From my tracker (below), propose today’s top 5 applications, fill missing ‘Next Action’, & draft follow-ups where Status=Applied & T+3 days.”
Copy-Paste Pack (Everything In One Place)
1) Google Alerts seeds
("Data Engineer" OR "Analytics Engineer") (dbt OR "semantic layer") (Snowflake OR BigQuery OR Redshift OR Databricks) (UK OR "Remote UK")
("Streaming Engineer" OR "Real-time") (Kafka OR Flink OR "Structured Streaming" OR Debezium OR Kinesis OR Pub/Sub OR "Event Hubs") (UK OR "Remote UK")
("Data Engineer" OR "Data Platform") (Databricks OR PySpark OR "Delta Live Tables" OR MLflow) (S3 OR ADLS OR GCS) (UK OR "Remote UK")
("DataOps" OR "Data Quality" OR "Data Observability") ("Great Expectations" OR Soda OR "Monte Carlo" OR Datafold OR DataHub OR OpenLineage) (UK OR "Remote UK")
("Data Governance" OR "Data Security" OR "Data Privacy") (GDPR OR PII OR masking OR "row-level security" OR IAM OR KMS) (UK OR "Remote UK")
("Graduate" OR "Junior" OR "Internship") ("data engineer" OR "analytics engineer") (SQL OR Python) (UK OR "Remote UK")
2) ATS-focused Google search
("Data Engineer" OR "Analytics Engineer" OR "Data Platform" OR "Streaming Engineer")
(site:boards.greenhouse.io OR site:lever.co OR site:workable.com OR site:ashbyhq.com OR site:smartrecruiters.com OR site:icims.com OR site:successfactors.com)
(UK OR "Remote UK")
3) Data Job Scout (short version)
You are my UK Data Job Scout. From pasted listings, remove duplicates, rank by fit to my criteria, and output:
• Summary (counts + scoring)
• Top 10 roles (Title — Company — Location — Link — Score — 1-line why)
• Per-role actions (3 CV bullets, 6–10 keywords, 3-sentence outreach)
Criteria: [paste your clusters & must-haves]
4) Deep-dive tailoring
Analyse this spec. Return: 3 tailored CV bullets (action+tool+impact), 10 keywords, a 120-word cover note referencing their stack & a 30-day quick win, & 6 interview Qs with model answers.
Spec: [paste] | Background: [paste]
5) Follow-up message
Please draft a concise follow-up for my application submitted on [date], referencing [one stack/pattern/SLA] from the spec & reaffirming my fit in 2 sentences.
Final Thoughts
Your edge isn’t endless scrolling—it’s consistent, high-quality execution. Put discovery on autopilot with alerts & RSS, let ChatGPT act as your Data Job Scout, & ship one excellent application each day. Mirror the stack & patterns the spec cares about, quantify improvements in latency, cost & reliability, keep tight feedback loops—& you’ll move from scanning feeds to booking interviews, fast.
If you want a quick win, start with this alert:
("Data Engineer" OR "Analytics Engineer") (dbt) (Snowflake OR BigQuery OR Databricks) (UK OR "Remote UK")
Paste the first batch into ChatGPT with your Data Job Scout prompt—& enjoy your first hour back this week.
