Senior Data Engineer Resume Example
The bar for senior data engineers: ownership of scalable system design and architectural judgment. Tool lists without clear design justifications get filtered out.
This resume is for senior data engineers who design complex data architectures and mentor junior talent, but aren't yet responsible for defining the global data roadmap or managing entire departments.
- Ownership of end-to-end data architecture and system design
- Evidence of technical leadership through mentorship or cross-functional influence
- Measurable impact on system reliability, latency, or infrastructure costs
- Summary scoped to architectural ownership and leadership
- Skills section categorized by technical domain and toolset
- Experience bullets ordered by business impact and scale
Kevin Roberts
Summary
Experience
- Designed and implemented a real-time streaming architecture using Flink and Kafka to ingest 2.4B daily events into Snowflake, reducing data latency from 30 minutes to sub-10 seconds.
- Optimized Spark processing jobs for the user analytics platform, reducing cloud compute costs by $315K annually through improved partition logic and memory management.
- Mentored 4 junior data engineers on data modeling patterns and CI/CD best practices, improving team deployment frequency by 28%.
- Spearheaded the migration of 18 legacy ETL pipelines to a modular dbt framework, improving data freshness for the product marketing team from 4 hours to 15 minutes.
- Built a centralized metadata management service in Python that automated schema validation for 14 upstream data sources, preventing approximately 12 breaking changes per month.
- Refined Airflow DAG scheduling and resource allocation for the internal experimentation platform, resulting in a 38% reduction in pipeline failure rates.
- Owned the implementation of a data quality framework using Great Expectations, covering 450+ critical tables across the enterprise warehouse.
- Scaled the core telemetry pipeline to support 1.2M monthly active users, enabling real-time product usage reporting for the engineering leadership team.
- Developed Python-based extractors for 5 third-party APIs, consolidating marketing and sales data into a unified Redshift warehouse for integrated reporting.
- Decreased query latency by 52% for the executive dashboard by implementing strategic indexing, materialized views, and query refactoring.
- Maintained 25+ Airflow workflows ensuring 99.9% uptime for daily reporting cycles across the finance and growth departments.
Education
Skills
Python · SQL · Airflow · Spark · AWS · Snowflake · dbt · Kafka · Flink · Redshift · Data Modeling · Data Architecture · Pipeline Optimization · Terraform · CI/CD
What makes this resume effective
- This resume meets the hiring bar for senior data engineers by demonstrating architectural ownership, cost-efficiency improvements, and technical mentorship.
- At Grammarly, Kevin Roberts reduced data latency from 30 minutes to sub-10 seconds using Flink and Kafka, proving he can design high-performance streaming systems.
- Notice how the HashiCorp experience highlights a 38% reduction in pipeline failure rates, which anchors his impact in system reliability and operational excellence.
How to write better bullet points
Managed Kafka and Spark pipelines for user data.
Designed a real-time streaming architecture using Flink and Kafka to ingest 2.4B daily events, reducing latency to sub-10 seconds.
It replaces a vague task with a specific architectural achievement and a massive, measurable performance outcome.
Mentored junior engineers on the team.
Mentored 4 junior data engineers on data modeling patterns, improving team deployment frequency by 28%.
It quantifies the mentorship effort and ties it to a tangible improvement in team productivity.
Fixed slow queries in Redshift.
Decreased query latency by 52% for the executive dashboard by implementing strategic indexing and query refactoring.
It specifies the exact methods used and the high-visibility impact on executive decision-making tools.
Senior Data Engineer resume writing tips
- Highlight architectural decisions that solved specific business bottlenecks or technical debt.
- Quantify how your technical mentorship directly improved team velocity or deployment frequency.
- Showcase optimizations that resulted in significant cloud cost savings or performance gains.
Common mistakes
- Focusing only on tools rather than the architectural 'why' behind their implementation.
- Failing to mention mentorship or peer review, which signals a lack of senior-level leadership.
- Listing maintenance tasks instead of proactive system improvements or migrations.
Frequently asked questions
Is this resume right for someone with 5 years of experience? Yes if you have led architectural migrations or mentored peers. No if your work is limited to executing tickets without owning the design.
Yes if you have led architectural migrations or mentored peers. No if your work is limited to executing tickets without owning the design.
Yes, if you have led architectural migrations or mentored peers. No, if your work is still primarily focused on completing assigned tickets without owning the underlying design.
What if my background isn't in a high-growth tech company like Grammarly? Yes, because technical patterns for scalability are universal. Focus on the volume of data handled and the complexity of the pipelines you built.
Yes, because technical patterns for scalability are universal. Focus on the volume of data handled and the complexity of the pipelines you built.
The technical patterns for scalability and reliability remain the same across industries. Focus on the volume of data you handled and the complexity of the pipelines you built.
What if I don't have access to exact cost-saving numbers like the $315K mentioned? Use percentages or scale indicators like event volume or throughput to illustrate magnitude when specific dollar amounts aren't available.
Use percentages or scale indicators like event volume or throughput to illustrate magnitude when specific dollar amounts aren't available.
You can use percentages or scale indicators to show impact. Kevin Roberts uses the 2.4B daily events metric to illustrate the magnitude of his work when specific dollars aren't the primary focus.
How much should I change before applying? Keep the high-impact bullet structure but swap technologies to match the job description and address the posting's specific architectural challenges.
Keep the high-impact bullet structure but swap technologies to match the job description and address the posting's specific architectural challenges.
Keep the structure of the high-impact bullets but swap the specific tech stack to match the job description. Ensure your summary reflects the specific architectural challenges mentioned in the posting.
What do hiring managers focus on at this level? They prioritize candidates who solve ambiguous problems and raise the team's technical bar through mentorship and cross-functional leadership.
They prioritize candidates who solve ambiguous problems and raise the team's technical bar through mentorship and cross-functional leadership.
They look for evidence that you can be trusted with ambiguous problems and can improve the technical bar of the entire team. This resume signals that through mentorship and cross-functional project leadership.
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