Mid-level Data Analytics Engineer

Nexiva • Alpharetta, GA

1d • Onsite

About The Position

The Technology Risk Controls Engineering team within Morgan Stanley's Technology Organization is seeking a Data Analytics Engineer to transform raw data from multiple sources into trusted, curated datasets and business metrics for analytics, reporting, and data applications. The role combines SQL, Python, and data engineering work across relational databases, analytical platforms, files, and APIs.

The engineer will prepare data for Power BI dashboards and Python-based applications, build repeatable and validated data pipelines, resolve data-quality issues, and work iteratively with business and technology stakeholders. The role also includes documenting data sources, transformation logic, business rules, and metric definitions. This is a mid-level position with approximately 3–5 years of relevant experience. The posting specifies Alpharetta, Georgia, local GC/USC candidates only, an in-person interview, and a C2C rate of $55–$60 per hour.

Requirements

• Strong SQL and relational database development skills.
• Hands-on experience with IBM DB2, Snowflake, and DuckDB.
• Proficiency in Python, including data manipulation with 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.
• 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 technical teams and business stakeholders.
• Demonstrated ability to deliver quality reporting solutions in a fast-paced, iterative environment.

Nice To Haves

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

Responsibilities

• Source and integrate data from IBM DB2, Snowflake, CSV and 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 Power BI dashboards and Python-based applications using Streamlit, Dash, or similar frameworks.
• Build repeatable data pipelines with 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.

What This Job Offers

• Career Level: Mid Level