Data Engineer

BAE SystemsFort Walton Beach, FL

About The Position

We are seeking an experienced Cloud Data Warehouse and AI/ML Engineer to design, build, and maintain large-scale data warehouses, ETL pipelines, and AI/ML models that drive data-driven decision-making. The successful candidate will have a strong background in data warehousing, ETL, and AI/ML, with experience in working with various tools.

Requirements

  • Bachelor's or Master's degree in Computer Science or a related field, with at least 6 years of experience in Information Technology
  • Proficiency in one or more programming languages (e.g., Python, Java, Scala)
  • 6+ years of experience in data engineering, with a focus on designing and implementing large-scale data systems
  • 5 + years of hands-on experience in writing complex, highly optimized queries across large data sets using AWS Redshift, Oracle and SQL Server.
  • 5 + years of hands-on experience using AWS Glue, python/spark to build ETL pipelines in a production setting, including writing test cases
  • Strong understanding of database design principles, data modeling, and data governance
  • Proficiency in SQL, including query optimization, indexing, and performance tuning
  • Experience with data warehousing concepts, including star and snowflake schemas
  • Strong analytical and problem-solving skills, with the ability to break down complex problems into manageable components
  • Experience with data storage solutions such as relational databases (Oracle, SQL Server), NoSQL databases and cloud-based data warehouses (Redshift)
  • Experience with data processing frameworks such as Apache Kafka, Fivetran
  • Experience in building ETL pipelines using AWS Glue, Apache Airflow, and programming languages including Python and PySpark
  • Understanding of data quality and governance principles and best practices
  • Experience with AWS services and best practices
  • Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams
  • Strong problem-solving and analytical skills, with the ability to break down complex problems into manageable components
  • Ability to work in a fast-paced environment and adapt to changing priorities
  • Strong attention to detail and ability to maintain high-quality documentation
  • Commitment to continuous learning and professional development

Nice To Haves

  • Experience with Dataiku
  • Experience with building reports using PowerBI and Tableau
  • Familiarity with agile development methodologies and version control systems such as Git
  • Certification in data warehousing, ETL, or AI/ML (e.g., Certified Data Warehouse Architect, Certified ETL Developer)
  • Experience with agile development methodologies such as Scrum or Kanban

Responsibilities

  • Design and implement data pipelines to ingest, extract, transform, load (ETL) data and store large data sets from various sources
  • Build and maintain data warehouses, including data modeling, data governance, and data quality
  • Ensure data quality, integrity, and security by implementing data validation, data cleansing, and data governance policies
  • Optimize data systems for performance, scalability, and reliability
  • Collaborate with customers to understand their technical requirements and provide guidance on best practices for using Amazon Redshift
  • Work with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and deliver data solutions
  • Provide technical support for Amazon Redshift, including troubleshooting, performance optimization, and data modeling
  • Integrate AI/ML models with ETL pipelines and data warehouses to enable predictive analytics and machine learning
  • Develop and deploy AI/ML models using popular frameworks such as TensorFlow, PyTorch, or Scikit-learn
  • Work with data scientists to develop and deploy data-driven products and features
  • Identify and resolve data-related issues, including data pipeline failures, data quality issues, and performance bottlenecks
  • Develop technical documentation and knowledge base articles to help customers and AWS engineers troubleshoot common issues

Benefits

  • health, dental, and vision insurance
  • health savings accounts
  • a 401(k) savings plan
  • disability coverage
  • life and accident insurance
  • employee assistance program
  • legal plan
  • discounts on things like home, auto, and pet insurance
  • paid time off
  • paid holidays
  • paid parental leave
  • military leave
  • bereavement leave
  • applicable federal and state sick leave
  • company recognition program to receive monetary or non-monetary recognition awards
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