Tomás Silva

Senior Data Engineer

Lisbon, Portugaltomas.silva@example.com+351 912 345 678linkedin.com/in/tomassilvagithub.com/tomassilva

Summary

Senior data engineer with 7 years building lakehouse platforms on Spark for mobility and banking. Makes data reliable, cheap and fast enough that analysts stop waiting, and treats pipelines like products with owners, contracts and tests. Databricks-certified.

Experience

Senior Data EngineerJan 2021 – Present

Canal MobilityLisbon

Migrated a 400 TB warehouse to a Delta Lake lakehouse, cutting compute costs 38% and query times from minutes to seconds.
Built streaming pipelines in Spark Structured Streaming delivering trip data within 2 minutes instead of next day.
Introduced data contracts and tests for 120 tables; broken dashboards fell from weekly to rare.
Designed a self-serve ingestion framework that let analysts add new sources in hours, not weeks.
Led a team of 4 engineers and ran the data platform's quarterly roadmap.
Cut pipeline failures 70% by adding retries, idempotent writes and clear ownership for every job.
Documented lineage for 200 critical tables so analysts could trace every metric to its source.

Data EngineerMay 2017 – Dec 2020

Atlântico BankPorto

Designed the first Airflow platform, now running 300 daily jobs.
Cut the nightly ETL window from 7 to 2 hours with partitioning and incremental loads.
Built GDPR deletion pipelines that processed 15,000 customer requests a year automatically.
Partnered with risk analysts to deliver a credit data mart used in 4 regulatory reports.
Reduced cloud storage costs €60k a year by archiving cold data to cheaper tiers.
Mentored 2 analysts who moved into data engineering roles.

BI DeveloperSep 2015 – Apr 2017

Atlântico BankPorto

Built 25 SQL Server reports for branch managers across 120 branches.
Optimised slow stored procedures, cutting report runtimes by an average of 70%.
Documented the data model for 80 core tables, onboarding new analysts twice as fast.
Automated data-quality alerts that caught 30 broken loads before users noticed.

Written for roles atDatabricks

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Why this résumé works

Cost and latency — the two numbers data platform teams are judged on.
Data quality work is shown by its effect (fewer broken dashboards).
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Bullet breakdown

Senior Data Engineer at Canal Mobility — what each line does right.

Migrated a 400 TB warehouse to a Delta Lake lakehouse, cutting compute costs 38% and query times from minutes to seconds.
Strong verb Number 1–2 lines
Built streaming pipelines in Spark Structured Streaming delivering trip data within 2 minutes instead of next day.
Strong verb Number 1–2 lines
Introduced data contracts and tests for 120 tables; broken dashboards fell from weekly to rare.
Strong verb Number 1–2 lines
Designed a self-serve ingestion framework that let analysts add new sources in hours, not weeks.
Strong verb Number 1–2 lines
Led a team of 4 engineers and ran the data platform's quarterly roadmap.
Strong verb Number 1–2 lines
Cut pipeline failures 70% by adding retries, idempotent writes and clear ownership for every job.
Strong verb Number 1–2 lines
Documented lineage for 200 critical tables so analysts could trace every metric to its source.
Strong verb Number 1–2 lines

Written by GotOffered as an example of a strong Data Engineer résumé for roles at companies like Databricks. The person and past employers are fictional. Not affiliated with or endorsed by Databricks; logos are trademarks of their owners.