Sr Data Engineer

We're looking for a Senior Data Engineer to build and modernize the data platform across an enterprise environment. This is a hands-on engineering role focused on building, not oversight. It fits someone who knows what good data engineering looks like, understands where the AWS data stack is headed, and can move work forward without much direction. The broader platform covers data lakes, analytical warehousing, and pipeline orchestration, and there is room to take on more scope over time. Please note! We place high value on collaboration and the value that in-person work offers. We need someone who can commit to three days onsite in Rosemont, just outside Chicago! WHAT YOU'LL DO Troubleshoot and support applications already running in production. This is a build-and-own role, not build-and-hand-off. Work across all phases of the software development life cycle: functional analysis, technical requirements, prototyping, coding, testing, deployment, and support. Participate in daily scrums and partner with the Scrum Master and QA team to hold delivery timelines and priorities. Solve problems independently with limited supervision, and serve as a go-to technical resource for other developers. Consistently deliver high-quality software and coach peers and junior team members. Step in to drive team activities for short stretches when leadership or the Scrum Master is out. Identify opportunities for technical improvement in specific processes or functional areas, recommend solutions, and advocate for their implementation. Influence technical design decisions and make recommendations on high-level architecture. WHAT YOU BRING We want a hands-on data engineer with real depth across the AWS data stack. Someone who has spent years building and running enterprise data platforms, not someone newer to the space. Bachelor's degree or equivalent. 6+ years working with enterprise data platforms, building and managing data lakes and working with big data technologies. 5+ years with relational and NoSQL databases, with advanced SQL knowledge. 4+ years on the AWS platform, solutioning across services like IAM, S3, API Gateway, Lambda, Glue, Lake Formation, Redshift, DynamoDB, and RDS. 4+ years using Python for data engineering and building high-performance, scalable data pipelines. 2+ years with Apache Airflow for orchestrating analytics workloads. 2+ years with Infrastructure-as-Code tools like Terraform or CloudFormation. Prior experience with traditional ETL tools like Talend Open Studio, Informatica, or Pentaho. Expert-level command of relational database concepts, SQL, logic modeling, best practices, and physical design. Expert at developing stored procedures, views, and dynamic SQL. Deep understanding of data warehousing, business intelligence, and data security. Proficiency in data catalog, data quality, master data management (MDM), and data governance best practices. A team player who is comfortable adopting newer technologies while continuing to support legacy systems. Strong analytical skills and clear written and verbal communication. NICE TO HAVE Experience with AWS EKS, setting up and managing Kubernetes clusters. Industry certifications on AWS and the other technologies in the stack. Experience in a SQL-based environment using SSIS, T-SQL, SSRS, .NET, and C#. Cloud DevOps experience with tools like GitLab, Bitbucket, or similar. MMD Services Inc. is an equal opportunity employer. All applicants are considered for all positions without regard to race, religion, color, sex, gender, sexual orientation, pregnancy, age, national origin, ancestry, physical/mental disability, medical condition, military/veteran status, genetic information, marital status, ethnicity, alienage or any other protected classification, in accordance with applicable federal, state, and local laws. #J-18808-Ljbffr