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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Expertise in designing and operating high-volume data pipelines with a focus on data quality, integrity, and security. Proficient in mentoring engineering teams and implementing best practices in data architecture and governance.
Highest-signal resume keywords
Data EngineeringGCP: BigQuery, Pub/Sub, DataflowPython and SQLInfrastructure as Code (Pulumi or Terraform)Real-Time Data Platform Design
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design, build, and operate high-volume, high-velocity data pipelines powering ViX
- Set architecture and multi-year technical direction for the data platform
- Stay hands-on with complex real-time and batch data problems
- Mentor junior and mid-level engineers and raise engineering standards
- Build reference implementations, frameworks, reusable libraries, ingestion templates, dbt and Airflow patterns, and Pulumi IaC modules
- Lead real-time pipeline design on Pub/Sub and Dataflow, including schemas, schema registry and evolution, exactly-once processing, watermarking, and late-data handling
- Own pipelines end to end from design and development through testing, deployment, and production support
- Ensure data quality, integrity, security, and availability
- Partner with Product Managers, Data Scientists, Analysts, and Engineering teams to translate business requirements into technical solutions
- Contribute to data architecture discussions and long-term platform strategy
- Identify process improvements and operational efficiencies
- Optimize storage, processing, orchestration, BigQuery query costs, and storage costs
- Monitor, troubleshoot, and resolve pipeline and platform issues; contribute to incident reviews
- Implement data governance, observability, testing, and CI/CD best practices
- Lead severe data incident response, run blameless postmortems, and drive systemic fixes
- Participate in code reviews, technical interviews, architectural decisions, and engineering best practices
- Evaluate and drive adoption of emerging technologies, including AI-assisted engineering workflows and LLM-enabled data tooling
Requirements
What you’ll need- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent experience
- 12+ years of experience in Data Engineering, Data Warehousing, or Big Data environments
- 2+ years in a Tech-lead role setting technical direction across teams
- Demonstrated experience mentoring and developing junior and mid-level engineers
- Proven track record designing and running real-time data platforms in production at high volume, for example billions of events per day
- Expert-level experience with GCP: BigQuery, Pub/Sub, Dataflow (Apache Beam), Cloud Composer (Airflow), and Cloud Storage; AWS experience will also be considered
- Expert-level Python and SQL, and production experience with dbt
- Deep knowledge of stream processing concepts: event time vs. processing time, windowing, watermarks, exactly-once delivery, and backpressure; Kafka, Flink, or Spark
- Expert understanding of data modeling for analytics, including dimensional modeling, event modeling, and lakehouse table formats such as Apache Iceberg
- Strong experience with Infrastructure as Code (Pulumi or Terraform), CI/CD, and automated testing for data pipelines
- Demonstrated ownership of data reliability: SLOs, data observability, incident management, and postmortems
- Demonstrated success reducing cloud data platform cost at scale
- Excellent written, verbal, and presentation skills, including design documents and communication with technical and executive audiences
- Must be authorized to work in the United States
- Applicants must be currently authorized to work in the United States on a full-time basis
- Employment/education will be verified
Benefits
Comp & perks- PTO
- Tuition reimbursement
- Wellness programs
- Employee support programs
- 401(k)
- Life insurance and other insurance plans
- Medical coverage
- Dental coverage
- Vision coverage
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data WarehousingBig Data EnvironmentsStream Processing ConceptsData Modeling for AnalyticsCI/CD Best PracticesAutomated Testing for Data PipelinesEvent ModelingDimensional ModelingLakehouse Table FormatsCloud Storage
Soft Skills
MentoringCommunication SkillsPresentation SkillsCollaborationProblem-Solving
Tools & Technologies
Apache BeamCloud Composer (Airflow)KafkaFlinkSparkPulumiTerraformCI/CD ToolsData Governance ToolsObservability Tools
Industry Keywords
Data QualityData IntegrityData SecurityIncident ManagementPostmortemsCloud Data Platform Cost ReductionTechnical DirectionProcess ImprovementsOperational EfficienciesData Architecture