Sr. Data Engineer
Onsite -Troy Michigan-Open to c2c

Duties and Responsibilities:

• The Sr. Data Engineer is responsible in 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.
• You will stay on top of tech trends, experiment with and learn new technologies, contribute to the growth of data organization, participate in internal & external technology communities, and mentor other members of the team.
• Provide technical leadership at every stage of the data engineering lifecycle, from designing data platforms, data pipelines, data stores, and gathering, importing, wrangling, querying, and analyzing data.
• The Sr Data Engineer will work closely with various customers including their immediate project teams, business domain experts and other technical staff members.
• Work daily within a project team environment, taking direction from project management and technical leaders.
• Responsible for design, development, administration, support, and maintenance of the Snowflake Platform and Oracle Platform.
• Participates in the full systems life cycle and cloud data lake/data warehouse design and build including recommendation of code development, integration with data marketplace or reuse and buy versus build solutions.

• Lead data integration across the enterprise thru design, build and implementation of large scale, high-volume, high-performance data pipelines for both on-prem and cloud data lake and data warehouses.
• Lead the development and documentation of technical best practices for ELT/ETL activities.
• Also, oversee a program inception to build a new product if needed.

• Lead the design of technical solution including code, scripts, data pipelines, processes/procedures for integration of data lake and data warehouse solutions in an operative IT environment.

• Ensures data engineering activities are aligned with scope, schedule, priority and business objectives.
• Oversees code development, unit and performance testing activities.
• Responsible to code and lead the team to implement the solution.

• Leads validation efforts by verifying the data at various middle stages that are being used between source and destination and assisting others in validating the solution performs as expected.
• Meets or exceeds all operational readiness requirements (e.g., operations engineering, performance, and risk management).
• Ensure compliance with applicable federal, state and local laws and regulations.
• Complete all required compliance training.
• Maintain knowledge of and adhere to client's internal compliance policies and procedures.
• Take responsibility to keep up to date with changing regulations and policies.

• High School Diploma, GED, or foreign equivalent required.
• Bachelor's in Computer Science, Mathematics or related field 7 years of development experience preferred, or 10 years comparable work experience required.
• 10 years of experience designing, developing, testing, and implementing Extract, Transform and Load (ELT/ETL) solutions using enterprise ELT/ETL
• 15 years of comparable work experience.
• 10 years of experience developing and implementing data integration, data lake and data warehouse solutions in an on-premise and cloud environment.
• 5 years of experience working with Business Intelligence tools (IBM Cognos is preferred), Power BI and Alteryx.
• 7 years of experience working with API’s, data as a service, data marketplace and data mesh.
• 10 years of experience with various Software Development Life Cycle methods such as Agile, SCRUM, Waterfall, etc.
• 3-year experience in 100 TB data environment.

• Proven experience developing and maintaining data pipelines and ETL jobs using IBM DataStage, Informatica, Matillion, FiveTran, Talend or Dbt
• Knowledge of AWS cloud services such as S3, EMR, Lambda, Glue, Sage Maker, Redshift & Athena and/or Snowflake.
• Experienced in data modelling for self-service business intelligence, advanced analytics, and user application.
• Experience with Data Science including AI/ML Engineering, ML framework/pipeline build and predictive/prescriptive analytics on Aws Sagemaker.
• Experience with migrating, architecting, designing, building and implementing cloud data lake, data warehouses (cloud/on-prem), data mesh, data as a service, and cloud data marketplace.
• Ability to communicate complex technical concepts by adjusting messaging to the audience: business partners, IT peers, external stakeholders, etc.
• Proven ability to design and build technical solutions using applicable technologies; ability to demonstrate exceptional data engineering skills.
• Ability to prioritize work by dividing time, attention and effort between current project workload and on-going day to day activities.
• Demonstrates strength in adapting to change in processes, procedures and priorities.
• Proven ability to establish a high level of trust and confidence in both the business and IT communities.
• Strong teamwork and interpersonal skills at all management levels.
• Proven ability to manage to a project budget.
• Experience applying agile practices to solution delivery.
• Must be team-oriented and have excellent oral and written communication skills.
• Strong analytic and problem-solving skills.
• Good organizational and time-management skills.
• Experience in Strategic Thinking and Solutioning.
• Must be a self-starter to understand existing bottlenecks and come up with innovative solution.
• Demonstrated ability to work with key stakeholders outside the project to understand requirements/resolve issues.
• Experience with data model design, writing complex SQL queries, etc., and should have a good understanding of BI/DWH principles.
• Expertise in Relational Database Management System, Data Mart and Data Warehouse design.
• Expert-level SQL development skills in a multi-tier environment.
• Expertise in flat file formats, XML within PL/SQL, and file format conversion.
• Strong understanding of SDLC and Agile Methodologies.
• Strong understanding of model driven development.
• Strong understanding of ETL best practices.
• Proven strength in interpreting customer business needs and translating them into application and operational requirements.
• Strong problem-solving skills and analytic skills with proven strength in applying root cause analysis.