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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data engineering, focusing on building and optimizing data pipelines, ensuring data quality, and implementing infrastructure as code. Proficient in leading technical teams and collaborating with stakeholders to drive strategic data initiatives.
Highest-signal resume keywords
Data Engineering LeadershipPython ProgrammingSQL ProficiencyGoogle Cloud TechnologiesData Quality Monitoring
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 ModellingBatch ProcessingNear-Real-Time PipelinesInfrastructure as CodeCI/CD for Data Pipelines
Soft Skills
Clear CommunicationMentoring Engineers
Tools & Technologies
BigQueryDataflowPub/SubComposer/AirflowTerraform
Industry Keywords
Data IngestionCanonical Data ModelData QualityGeographic EnrichmentFeature Pipelines
Tech Stack
Tools & technologiesAirflowBigQueryCloudPythonSQLTerraform
About the role
Key responsibilities & impact- Lead the squad technically by setting engineering standards, guiding design decisions, reviewing code and unblocking the team
- Work with the Solution Architect on design authority and integration contracts
- Build ingestion for multiple feeds, including high-frequency telemetry with historical backfill, customer support data, business data and third-party performance data
- Design a canonical data model with cross-source validation
- Build data quality, freshness and completeness monitoring
- Serve curated marts and feature pipelines for the ML team
- Scale ingestion to high-volume, granular data with geographic enrichment and aggregation hierarchies
- Automate business data feeds from source systems
- Build data marts supporting strategic commercial decisions
- Partner with platform engineering on the Google Cloud landing zone, infrastructure as code, CI/CD, observability and cost guardrails
- Guide the engineering team day to day alongside the Solution Architect
Requirements
What you’ll need- Significant commercial data engineering experience, including time technically leading a team or workstream
- Strong Python and SQL
- Hands-on experience building batch and near-real-time pipelines on a cloud platform, ideally Google Cloud
- Experience with BigQuery, Dataflow, Pub/Sub, Composer/Airflow or similar Google Cloud technologies
- Strong data modelling skills, including joining and reconciling data from multiple sources
- Experience implementing data quality, freshness and completeness monitoring
- Experience with infrastructure as code, such as Terraform
- Experience with CI/CD for data pipelines
- Clear communication with client stakeholders
- Experience mentoring engineers
Benefits
Comp & perks- Hybrid working arrangement
- Collaborative team environment
- Mentoring and guidance opportunities
- Work on a greenfield AI-driven platform
- Exposure to Google Cloud technologies and modern data engineering practices