Data Engineer

Metas Solutions•, GA

About The Position

Metas Solutions has an "immediate opening" for a talented Data Engineer to provide specialized Data Engineering support to build, optimize, and maintain cloud‑based data pipelines, platforms, and data stores that enable analytics across large, diverse datasets. This role includes designing scalable ETL/ELT workflows, structuring data storage architectures, and ensuring reliable data ingestion from multiple structured and unstructured sources. You'll support mission‑driven analytics efforts by transforming raw data into analysis‑ready formats, performing backend SQL/NoSQL testing, and validating data quality throughout the pipeline lifecycle. In this position, you will collaborate with analysts, product teams, and developers to understand evolving data requirements, define technical specifications, and implement end‑to‑end solutions supporting reporting, modeling, and visualization needs.

Requirements

3+ years of experience in Data Warehouse development
3+ years of experience with data analysis of aggregated data from multiple sources in cloud-based environments
2+ years of experience developing and maintaining scalable data stores that supply big data in forms needed for business analysis
Experience with SQL and Python for retrieving, parsing, and processing structured and unstructured data
Experience developing scalable ETL or ELT workflows for reporting and analytics using cloud-based technologies
Experience with using Cloudera or Hadoop technologies to ingest, transform, and process data
Experience leveraging generative AI coding tools to assist in development
Ability to perform backend SQL and NoSQL database testing, including post-deployment and data validation testing
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor's degree
Must be a U.S. Citizen or Lawful Permanent Resident (Green Card Holder)

Nice To Haves

Experience creating solutions within a collaborative and cross-functional team environment
Experience with AWS Glue, AWS Athena, and Postgres
Experience with distributed data and computing tools such as Spark, Databricks, Hive, AWS EMR, or Kafka
Experience working on real-time data and streaming applications
Experience with NoSQL implementation using MongoDB or Cassandra
Experience with data warehousing, including AWS Redshift, MySQL, or Snowflake
Experience with UNIX and Linux, including basic commands and Shell scripting
Experience with Agile engineering practices

Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver structured and unstructured data from multiple cloud‑based sources.
Build and optimize data storage solutions (data warehouses, data lakes, or lake houses) that support large‑scale analytics, reporting, and business intelligence needs.
Perform backend SQL and NoSQL testing, including data validation, post‑deployment checks, and troubleshooting of ingestion or schema issues.
Collaborate cross‑functionally with analysts, engineers, and stakeholders to translate requirements into technical data models, workflows, and pipeline specifications.
Develop scripts and automation to convert diverse data types into usable formats, while scaling, monitoring, and operating cloud‑based data platforms.