Big data engineer with 8 years of experience processing petabyte-scale event data for telecom and adtech. Optimized Spark jobs over 3 PB of network data, cutting cluster costs by 48%. Brings distributed systems tuning, streaming architecture and the patience to debug skewed joins and shuffle failures.
Experience
Big Data Engineer, Lonestar Wireless (Dallas, TX)
Jul 2021 – Present
Tuned Spark jobs over 3 PB of network telemetry with salting and adaptive query execution, cutting EMR costs 48%
Built a Flink streaming pipeline processing 2M events per second for real-time outage detection
Moved Hive tables to Apache Iceberg, enabling time travel and cutting full-table rewrites
Partnered with network operations to deliver dashboards that shortened outage detection from 20 minutes to 2
Data Engineer, Pixelpoint Ad Network (Austin, TX)
May 2018 – Jun 2021
Maintained a 300-node Hadoop cluster ingesting 20 TB of bid logs daily
Rewrote MapReduce reporting jobs in Spark, cutting runtimes from 7 hours to 50 minutes
A strong Big Data Engineer resume shows the systems you built, the scale they run at, and the measurable effect on speed, reliability or cost. Put your most relevant recent role first and make every bullet show a result, not a duty.
Sections, in order
Summary
Experience
Projects
Skills
Education
Length: One page for most candidates; move to two only if every line is relevant.
Summary: Write two or three lines: your role, your strongest skills, and one result that proves them.
Skills to feature
Programming languages
System design
Cloud platforms (AWS, GCP, Azure)
CI/CD
Testing and code review
Databases and SQL
Observability
Security fundamentals
APIs and integrations
Technical documentation
Example bullet points
Rebuilt the checkout service in Go, cutting p95 latency from 900 ms to 180 ms for 2M monthly users
Introduced contract tests and staged rollouts, reducing production incidents by 45% in two quarters
Migrated 30 services to Kubernetes with Terraform, lowering cloud spend by $250k a year
Tips from recruiters
Group skills by category (for example "Languages: Go, TypeScript") so recruiters and ATS parsers find them quickly.
Link to a repository, demo or write-up for at least one project you can talk about in depth.
Name the stack inside each bullet; keyword matching happens at the bullet level, not only in the skills list.
Recommended templates
Classic (ATS-friendly): Jake's-style LaTeX classic: small caps and hairline rules
Tech (ATS-friendly): Developer style: mono headings and tags, sans body
Modern (ATS-friendly): Clean single column with accent headings and rules
Big Data Engineer resume FAQ
What should a Big Data Engineer resume include?
A Big Data Engineer resume should show the systems you built, the scale they run at, and the measurable effect on speed, reliability or cost. Use these sections in this order: Summary, Experience, Projects, Skills and Education. Put your most relevant recent role first and make every bullet show a result, not a duty.
What is the best resume template for a Big Data Engineer?
Classic, Tech and Modern work well for Big Data Engineer roles. They are single-column with standard headings, so applicant tracking systems (ATS) parse them reliably.
How long should a Big Data Engineer resume be?
One page for most candidates; move to two only if every line is relevant.
Which skills should a Big Data Engineer put on a resume?
Prioritize the skills named in the job posting. Common ones for Big Data Engineer roles are Programming languages, System design, Cloud platforms (AWS, GCP, Azure), CI/CD, Testing and code review and Databases and SQL.
How do I write strong Big Data Engineer resume bullet points?
Start with an action verb, say what you did, and end with a measurable result such as latency, uptime and deploy frequency. For example: "Rebuilt the checkout service in Go, cutting p95 latency from 900 ms to 180 ms for 2M monthly users."