Think Beyond The Label Jobs

Data Engineer Job ID 2025-27815 Category Analytics/ Data Analysis Location US-OH-Cincinnati About DMI DMI is a leading provider of digital services and technology solutions, headquartered in Tysons Corner, VA. With a focus on end-to-end managed IT services, including managed mobility, cloud, cybersecurity, network operations, and application development, DMI supports public sector agencies and commercial enterprises around the globe. Recognized as a Top Workplace, DMI is committed to delivering secure, efcient, and cost-effective solutions that drive measurable results. Learn more at www.dminc.com About the Opportunity DMI, LLC is seeking a Data Engineer to join us. We are seeking a Data Engineer to help build, optimize, and scale our data pipelines, optimize data ingestion, transformation, and analysis of complex telecom data. This role will be instrumental in integrating large-scale invoices, usage records, and cost allocations into our AWS-based analytics platform while ensuring data integrity and performance. Duties and Responsibilities: Develop and maintain scalable ETL/ELT pipelines to process large volumes of telecom and financial data from carriers, APIs, and external sources. Design and optimize data models for structured and semi-structured data in PostgreSQL, Redshift, and other databases. Automate data processing workflows to improve efficiency and accuracy in processing telecom invoices, CDRs (Call Detail Records), and billing data. Ensure data quality and integrity, implementing error handling, validation, and reconciliation techniques. Optimize query performance and database structures to support analytics and reporting needs. Collaborate with cross-functional teams including Product, Engineering, DevOps, and Expense Management to understand data requirements and ensure alignment with business goals. Implement monitoring and logging solutions for data pipelines, ensuring reliability and auditability. Work with cloud-based infrastructure in AWS, utilizing services like Lambda, S3, Glue, Redshift, RDS, and Step Functions. Integrate machine learning capabilities into the data pipeline to enhance automation and predictive analytics. Qualifications Education and Years of Experience: Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field (or equivalent experience). A Master's degree in Data Science, Analytics, or Cloud Computing is a plus but not required. Relevant certifications in AWS (e.g., AWS Certified Data Analytics, AWS Certified Solutions Architect) or database technologies (e.g., PostgreSQL, Redshift, Snowflake) are a plus. 3+ years of experience as a Data Engineer, working with large-scale data processing. Proficiency in Python, SQL, and data transformation frameworks (e.g., dbt, Apache Airflow, or similar). Experience working with AWS cloud services (Lambda, S3, Glue, Redshift, RDS, Step Functions). Strong understanding of ETL/ELT methodologies, data warehousing, and database optimization. Experience with handling large telecom invoices, parsing carrier billing formats, and reconciling financial data is a plus. Experience integrating data from APIs, flat files, XML, JSON, and databases. Knowledge of data governance, compliance, and security best practices. Familiarity with data lake architecture and multi-tenant SaaS platforms. Strong problem-solving and analytical skills, with the ability to debug and optimize complex data processes. Required and Desired Skills/Certifications: Experience with big data technologies such as Spark, Snowflake, or Hadoop. Prior experience working in Telecom Expense Management (TEM) or FinTech. Exposure to DevOps principles, CI/CD pipelines, and infrastructure-as-code to