Data Analytics Engineer

Position: Data Analytics Engineer

Location: Alpharetta, GA (in person interview must)

Duration: 12 Months

The ideal candidate combines strong SQL, Python, and data engineering skills with experience across relational databases, analytical platforms, files, and APIs.

Key Responsibilities

• Source and integrate data from IBM DB2, Snowflake, CSV/Parquet files, JSON/REST APIs, and other data sources.
• Use SQL, Python, and DuckDB to cleanse, join, transform, aggregate, and curate data.
• Develop reusable datasets, metrics, KPIs, and analytical data models.
• Prepare data for consumption by Power BI dashboards and Python-based applications using Streamlit, Dash, or similar frameworks.
• Build repeatable data pipelines with appropriate validation, reconciliation, logging, and error handling.
• Identify and resolve data-quality and consistency issues across source systems.
• Rapidly prototype and iterate on data solutions with business and technology stakeholders.
• Document data sources, transformation logic, business rules, and metric definitions.

Required Skills

• Strong SQL and relational database development skills.
• Hands-on experience with IBM DB2, Snowflake, and DuckDB.
• Proficiency in Python, including data manipulation using pandas or similar libraries.
• Experience working with CSV, JSON, Parquet, REST APIs, and relational databases.
• Understanding of data modeling, transformation, data quality, and metric/KPI development.
• Experience preparing data for Power BI or custom analytical applications.
• Familiarity with Git and modern software development practices.
• Experience using GenAI development tools, such as GitHub Copilot, Anthropic Claude, OpenAI Codex, or similar tools, to accelerate development, testing, debugging, and documentation.

Preferred Experience

Experience with several of the following is beneficial:

• dbt or SQLMesh for data transformations
• FastAPI for sharing data via APIs
• Streamlit or Dash for custom data dashboards
• Power BI
• CI/CD and automated testing
• Cloud data and analytics platforms

Qualifications

• Approximately 3–5 years of relevant experience in data engineering, analytics engineering, BI, or software development.
• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Analytics, or a related discipline, or equivalent practical experience.
• Strong communication skills and the ability to work with both technical teams and business stakeholders.
• Demonstrated ability to deliver quality reporting solutions in a fast-paced, iterative environment.