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Tech Stack
Tools & technologiesAWSCloudETLPythonSparkSQL
About the role
Key responsibilities & impact- Provide technical feasibility analysis and solution evaluation for data and analytics initiatives
- Lead the design and implementation of scalable data engineering solutions, including data pipelines, data models, data integrations, and analytics-ready data products
- Provide technical leadership for data architecture, ETL/ELT design, code reviews, performance tuning, production support, and issue resolution
- Guide modernization of legacy data and reporting platforms, including migration from traditional ETL and reporting tools to modern cloud data platforms
- Design and oversee data pipelines using cloud-based technologies, Python, Spark, SQL, and related orchestration and transformation tools
- Support enterprise analytics platforms, including data warehouse, reporting, semantic layer, and business intelligence environments
- Partner with stakeholders to define and execute the technical roadmap for data engineering, analytics enablement, platform modernization, data quality, and automation
- Establish and promote engineering standards, reusable patterns, coding guidelines, testing practices, data quality controls, and documentation expectations
- Mentor engineers and technical team members, supporting skill development in cloud data engineering, data modeling, analytics engineering, and modern data platform practices
Requirements
What you’ll need- Bachelor’s degree in computer science, information systems, data engineering, analytics, engineering, or equivalent training and experience
- 12+ years of experience in software engineering, data engineering, analytics engineering, or enterprise data platform development
- Strong experience with Python, SQL, distributed data processing, and ETL/ELT development
- Experience with cloud-based data platforms and services, preferably AWS
- Experience with enterprise data warehouses, data marts, reporting platforms, and business intelligence solutions
- Strong understanding of data modeling, data warehousing, data quality, metadata management, data lineage, performance optimization, and production support practices
- Working knowledge of AI/ML concepts and data engineering practices
Benefits
Comp & perks- Flexible work environment
- Purpose, well-being, and work-life balance
- Opportunities for internal mobility
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonSQLETLELTdata modelingdata warehousingdata qualitymetadata managementperformance optimizationdistributed data processing
Soft Skills
technical leadershipmentoringstakeholder engagementproblem solvingcommunicationcollaborationdocumentationstandardizationguidanceskill development
Certifications
Bachelor’s degree in computer scienceBachelor’s degree in information systemsBachelor’s degree in data engineeringBachelor’s degree in analyticsBachelor’s degree in engineering
