Data/ETL Developer (Hybrid)

Job Title: Data/ETL Developer (Hybrid with 40% onsite) Location: Baltimore City, MD or Linthicum, MD Duration: up to 2 Years Client - Maryland Department of Health (MDH) The MDH office of Enterprise Technology MD Think Benefits Department - Center of Medicare & Medicaid Services (CMS), Worker Portal Project Position Description: Responsible for designing, building, and maintaining data pipelines and infrastructure to support data-driven decisions and analytics. The individual is responsible for the following tasks: • Design, develop and maintain data pipelines, and extract, transform, load (ETL) processes to collect, process and store structured and unstructured data • Build data architecture and storage solutions, including data lakehouses, data lakes, data warehouse, and data marts to support analytics and reporting • Develop data reliability, efficiency, and qualify checks and processes • Prepare data for data modeling • Monitor and optimize data architecture and data processing systems • Collaboration with multiple teams to understand requirements and objectives • Administer testing and troubleshooting related to performance, reliability, and scalability • Create and update documentation Additional Responsibilities: In addition to the responsibilities listed above, the individual will also be expected to perform the following: Data Architecture and Modeling: • Design and implement robust, scalable data models to support PMM application, analytics, and business intelligence initiatives • Optimize data warehousing solutions and manage data migrations in the AWS ecosystem, utilizing Amazon Redshift, RDS, and DocumentDB services ETL Development: • Develop and maintain scalable ETL pipelines using AWS Glue and other AWS services to enhance data collection, integration, and aggregation • Ensure data integrity and timeliness in the data pipeline, troubleshooting any issues that arise during data processing Data Integration: • Integrate data from various sources using AWS technologies, ensuring seamless data flow across systems • Collaborate with stakeholders to define data ingestion requirements and implement solutions to meet business needs Performance Optimization: • Monitor, tune, and manage database performance to ensure efficient data loads and queries • Implement best practices for data management within AWS to optimize storage and computing costs Security and Compliance: • Ensure all data practices comply with regulatory requirements and department policies • Implement and maintain security measures to protect data within AWS services Team Collaboration and Leadership: • Lead and mentor junior data engineers and team members on AWS best practices and technical challenges • Collaborate with UI/API team, business analysts, and other stakeholders to support data-driven decision- making Innovation and Continuous Improvement: • Explore and adopt new technologies within the AWS cloud to enhance the capabilities of the data platform • Continuously improve existing systems by analyzing business needs and technology trends Education: • This position requires a bachelor’s or master’s degree from an accredited college or university with a major in computer science, statistics, mathematics, economics, or related field. • Three (3) years of equivalent experience in a related field may be substituted for the Bachelor’s degree. General Experience: • The proposed candidate must have a minimum of three (3) years of experience as a data engineer. Specialized experience: 1. The candidate should have experience as data engineer or similar role with a strong understanding of data architecture and ETL processes. 1. The candidate should be proficient in programming languages for data processing and knowledgeable of distributed computing and parallel processing. • Minimum 5 + years ETL coding experience • Proficiency in programming languages such as Python and SQL for data processing and automation • Experience with distributed computing frameworks like Apache Spark or similar technologies • Experience with AWS data environment, primarily Glue, S3, DocumentDB, Redshift, RDS, Athena, etc. • Experience with data warehouses/RDBMS like Redshift and NoSQL data stores such as DocumentDB, DynamoDB, OpenSearch, etc • Experience in building data lakes using AWS Lake Formation • Experience with workflow orchestration and scheduling tools like AWS Step Functions, AWS MWAA, etc.. • Strong understanding of relational databases (including tables, views, indexes, table spaces) • Experience with source control tools such as GitHub and related CI/CD processes • Ability to analyze a company’s data needs • Strong problem-solving skills • Experience with the SDLC and Agile methodologies