Lead Data Engineer
Role Summary
Key Responsibilities
- Technical Leadership & Delivery: Drive solution design, work planning, and execution across the full SDLC; ensure high-quality releases and measurable outcomes.
- Oracle Engineering: Design robust schemas and write efficient SQL/PL/SQL; implement indexes/partitioning; manage performance tuning and query optimization.
- Performance & Reliability: Diagnose bottlenecks across application, database, and data pipelines; instrument, benchmark, and optimize for throughput and latency.
- Data Engineering: Build scalable transformations using Python (pandas) and Spark/PySpark; develop resilient ETL/ELT workflows and data quality checks.
- Application Development: Create maintainable Python services, libraries, and automation scripts; enforce clean architecture, testing, and code review practices.
- CI/CD & DevOps: Implement build/test/deploy pipelines (e.g., Jenkins/GitHub Actions); manage containerized workloads (Docker/Kubernetes) and infrastructure-as-code where appropriate.
- Mentorship & Collaboration: Coach junior engineers, set standards, and foster a culture of craftsmanship, accountability, and continuous improvement.
- Documentation & Governance: Maintain clear technical documentation, design records, and runbooks; contribute to data modeling conventions and development guidelines.
Core Skills
- Experience: 5+ years in software/data engineering with demonstrable impact in production environments.
- Oracle & SQL Mastery: Advanced SQL/PL/SQL, schema design, indexing strategies, partitioning, query tuning, and database observability.
- Python & Spark: Strong Python (including pandas) and practical Spark/PySpark for batch/stream processing and data transformation.
- Data Modeling: Ability to design logical and physical models (3NF, dimensional/star schema), define entities/relationships, and optimize for analytics or OLTP.
- CI/CD & Containers: Hands-on with modern pipelines and container orchestration (e.g., Jenkins/GitHub Actions, Docker, Kubernetes).
- Performance Engineering: Systematic approach to profiling, benchmarking, and optimization across app/data layers.
- Communication & Leadership: Clear written/verbal communication; proven collaboration and mentorship of junior team members.
Preferred Qualifications
- Cloud Expertise: Experience with AWS/Azure/GCP services (e.g., object storage, managed databases, compute, IAM/networking basics).
- Certifications (nice to have): Oracle Database, Python, Kubernetes/CKA/CKAD, or CI/CD tooling.
- Ways of Working: Familiarity with Agile/Scrum, trunk-based development, and test automation.
- Education: Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
- Travel: Occasional-primarily for team or stakeholder workshops.
Locations:
- Saint Petersburg, FL
- Denver, CO
- Memphis, TN
- Southfield, MI
Please note that this firm is not able to sponsor now or in the future.
FAQs
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Yes. Even if this role isn’t a perfect match, applying allows us to understand your expertise and ambitions, ensuring you're on our radar for the right opportunity when it arises.
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That's why we recommend registering your CV so you can be considered for roles that have yet to be created.
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