ETL Data Engineer

Location: Troy, MI (Hybrid)

About the Role

The Sr. Data Engineer is responsible for understanding and supporting the businesses through the design, development, and execution of Extract, Transform, and Load (ELT/ETL), data integration, and data analytics processes across the enterprise. This role involves staying on top of tech trends, experimenting with and learning new technologies, contributing to the growth of the data organization, participating in internal and external technology communities, and mentoring other team members.

Provide technical leadership at every stage of the data engineering lifecycle, from designing data platforms, data pipelines, and data stores to gathering, importing, wrangling, querying, and analyzing data. The Sr. Data Engineer will work closely with various stakeholders, including project teams, business domain experts, and other technical staff members.

Responsibilities

• Lead data integration across the enterprise through the design, build, and implementation of large-scale, high-volume, high-performance data pipelines for both on-prem and cloud data lakes and data warehouses.
• Lead the development and documentation of technical best practices for ELT/ETL activities and oversee program inception to build new products as needed.
• Design technical solutions, including code, scripts, data pipelines, and processes/procedures for integration of data lake and data warehouse solutions in an operative IT environment.
• Ensure data engineering activities align with scope, schedule, priority, and business objectives; oversee code development, unit, and performance testing activities.
• Lead validation efforts by verifying data at various stages between source and destination and assist in validating solution performance.
• Meet or exceed all operational readiness requirements (e.g., operations engineering, performance, and risk management).
• Design, develop, administer, support, and maintain the Snowflake Platform and Oracle Platform.
• Participate in full systems life cycle and cloud data lake/data warehouse design and build, including recommending code development, integration with data marketplace, or reuse and buy vs. build solutions.
• Ensure compliance with applicable federal, state, and local laws and regulations; complete required compliance training and adhere to internal policies.

Requirements

• High School Diploma, GED, or foreign equivalent required; Bachelor’s in Computer Science, Mathematics, or related field + 10 years of development experience preferred, or 10+ years of comparable work experience.
• 10+ years of experience designing, developing, testing, and implementing ELT/ETL solutions using enterprise ELT/ETL tools (e.g., IBM DataStage, Informatica).
• 10+ years of experience developing and implementing data integration, data lake, and data warehouse solutions in on-premise and cloud environments.
• 5+ years of experience with Business Intelligence tools (IBM Cognos preferred), Power BI, and Alteryx.
• 7+ years of experience working with APIs, data as a service, data marketplace, and data mesh.
• 10+ years of experience with Software Development Life Cycle methods such as Agile, SCRUM, Waterfall, etc.
• 3+ years of experience in a 100+ TB data environment.
• Proven experience developing and maintaining data pipelines and ETL jobs using tools like Matillion, FiveTran, Talend, or Dbt.
• Knowledge of AWS cloud services (e.g., S3, EMR, Lambda, Glue, SageMaker, Redshift, Athena) and/or Snowflake.
• Experience with data modeling for self-service business intelligence, advanced analytics, and user applications.
• Experience with Data Science, including AI/ML Engineering, ML framework/pipeline build, and predictive/prescriptive analytics on AWS SageMaker.
• Experience migrating, architecting, designing, building, and implementing cloud data lakes, data warehouses (cloud/on-prem), data mesh, data as a service, and cloud data marketplaces.
• Ability to communicate complex technical concepts to diverse audiences (business partners, IT peers, external stakeholders).
• Proven ability to design and build technical solutions using applicable technologies and exceptional data engineering skills.
• Strong SQL development skills in a multi-tier environment and expertise in Relational Database Management Systems, Data Mart, and Data Warehouse design.
• Expertise in flat file formats, XML within PL/SQL, and file format conversion.
• Strong understanding of SDLC, Agile Methodologies, model-driven development, and ETL best practices.
• Proven ability to interpret customer business needs and translate them into application and operational requirements.
• Strong problem-solving, analytic, and root cause analysis skills.
• Strong teamwork, interpersonal, and communication skills (oral and written).
• Experience applying agile practices to solution delivery and managing project budgets.
• Must be team-oriented, self-starting, and capable of strategic thinking and innovative problem-solving.

Skills

• Strong SQL and Python scripting.
• Proficiency in Snowflake, IBM DataStage, and Informatica.
• Experience in banking or financial services (recent experience required).
• Ability to prioritize work and adapt to changing processes, procedures, and priorities.
• Good organizational and time-management skills.