Lead Data Engineer

Lead Data Engineer

Department: Product Architecture 

Reports to: Manager, Data Engineering 

The Lead Data Engineer is responsible for ensuring the ongoing data needs of the organization are met through business intelligence, data warehousing, ETLs, data pipelining, and data integrations. This involves leading a team development effort for the creation of new features as well as maintenance and support of existing features. The Lead Data Engineer is tasked with developing and maintaining complex data pipelines that will combine data from multiple sources to populate data warehouses. The Lead Data Engineer is also responsible for business intelligence, as well as optimization and tuning of database queries. The Lead Data Engineer is an expert of our data in multiple areas and provides insight into our data for business decisions to be made by an internal or external consumer of this data.  

Responsibilities :  

• Gather requirements; compile data; prepare and analyze results; distribute reports  
• Interface with developers, product managers, and business analysts to understand data needs  
• Combine data from a variety of sources for use in reporting, research, and support decision-making  
• Develop, design, and launch new data extraction, transformation, and loading processes in production  
• Develop, design, and test complex program logic in order to produce analytical reports  
• Develop, design, implement and maintain data pipelines  
• Ensure data integrity; develop and produce reports utilized in measuring data accuracy  
• Troubleshoot data issues, validate result sets, recommend and implement process improvements  
• Improve performance and value of existing reports  
• Design and support production of new reporting processes  
• Overseeing team development efforts on multiple projects  

Requirements: 

• Bachelor’s degree in a technical field such as Computer Science or Mathematics required. Master’s degree preferred. 
• AWS Solutions Architect or Data Architect Certification preferred 
• Modern Architecture experience with the following tech stack: 
  • AWS: Glue, Lambda, Step Fxns, S3, Lake Formation, AWS Gateway  
  • Data Engineering: Python, Spark, Python libraries such as Pandas, NumPy, BeautifulSoup, SQLAlchemy, AirFlow, Iceberg, Avro, Parquet 
  • DevOps: Kubernetes, Helm, Terraform, GitHub Actions, Jenkins 
  • Java Skills: Experience coding in Java. Nice to have: Maven, TestNG, JUnit, DBUnit 
• Strong SQL development skills, including SQL query writing, performance tuning, and understanding of multiple SQL variants (e.g. MSSQL, PostgreSQL)  
• Experience with visualization tools (e.g. Power BI, Tableau, Sisense)  
• Fluency in at least one OOP language (Python preferred)  
• Strong understanding of data warehousing design concepts and data modeling  
• Strong understanding of custom ETL design, implementation, and maintenance  
• Experience with data pipeline design, development, and maintenance  
• Strong experience with data integration tools (e.g. SSIS, Streamsets, Informatica)  
• Experience in data analysis to help identify deliverables, gaps, and inconsistencies  
• Excellent verbal and written communication skills   
• Team player with a positive attitude and energy   
• A collaborative mindset  
• Ability to learn as you go 

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As set forth in Suvoda’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

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