Senior Data Engineer joining Reconomy to design, build and optimize data pipelines for an international circular economy specialist.
About the role
- Senior Data Engineer designing and operating scalable data pipelines on Google Cloud Platform. Leading data governance and collaborating with cross-functional teams for optimized data solutions.
Responsibilities
- Design and implement end-to-end data pipelines (ETL/ELT) that ingest, process, and curate large-scale enterprise data, including telemetry/vehicle data and other structured/unstructured sources.
- Migrate and modernize data assets to a centralized data platform (e.g., BigQuery) using principled data lake/warehouse architectures (Bronze/Silver/Gold or Medallion architecture) to power analytics and reporting.
- Architect scalable data models and data warehouses, optimizing for query performance, maintainability, and cost efficiency.
- Develop and operate robust orchestration pipelines using Airflow/Astronomer or Schedule Query, with secure, reproducible CI/CD workflows (Terraform + Git).
- Build and maintain reliable data quality checks, lineage, and monitoring with observability tools (e.g., Splunk, Looker/Grafana/Tableau/Power BI dashboards) to rapidly detect and resolve data issues.
- Implement data governance, security, and compliance controls (data lineage, access controls, PII/PHI protection) in collaboration with security and privacy teams.
- Lead the design and delivery of analytics-ready data assets for cross-functional teams, including dashboards, alerts, and self-service analytics.
- Mentor and coach junior engineers, review code, and drive best practices in data engineering, testing, and documentation.
- Collaborate with data scientists, product managers, and business stakeholders to translate requirements into scalable data solutions and timely insights.
- Monitor cost and capacity planning for cloud resources; optimize storage and compute usage across GCP services (BigQuery, Dataflow, Dataproc, GCS).
- Participate in on-call rotations and incident response to maintain high availability of data services.
Requirements
- Bachelor's Degree and/or equivalent education and experience
- 7+ years of experience in data engineering, data platforms, or a similar role.
- 4+ years of hands-on experience with Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Dataproc; Schedule Query or equivalent scheduling/orchestration).
- 4+ years experience in Python and SQL; strong experience with PySpark is a plus.
- 4+ years experience with ETL/ELT design, data modeling, data warehousing, and data governance.
- Practical experience building and operating data pipelines with orchestration tools (Airflow/Astronomer; Schedule Query).
- Experience with infrastructure-as-code and CI/CD (Terraform, Git, and related tooling).
- Demonstrated ability to design and implement analytics-ready data assets and dashboards; familiarity with BI tools (Looker, Tableau, Power BI, Grafana) for monitoring and reporting.
- Strong communication skills and ability to work effectively with cross-functional teams (engineering, analytics, product, security).
Benefits
- Immediate medical, dental, vision and prescription drug coverage
- Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
- Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
- Vehicle discount program for employees and family members and management leases
- Tuition assistance
- Established and active employee resource groups
- Paid time off for individual and team community service
- A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
- Paid time off and the option to purchase additional vacation time.
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