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Job Description

We are seeking a seasoned Data Warehouse Engineer with extensive experience in ETL (Extract, Transform, Load) development and AI/ML (Artificial Intelligence/Machine Learning) integration. The successful candidate will be responsible for designing, building, and maintaining large-scale data warehouses, ETL pipelines, and AI/ML models that enable data-driven decision-making. The ideal candidate will have a strong background in data warehousing, ETL, and AI/ML, with experience working with various technologies and tools.

Key Responsibilities:

• Design and implement data pipelines to ingest, extract, transform, load (ETL) data and store large datasets 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

Required Education, Experience, & Skills

• Bachelor's or Master's degree in Computer Science or a related field, with at least 8 years of experience in Information Technology

• Proficiency in one or more programming languages (e.g., Python, Java, Scala)

• 8 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 Oracle, SQL Server and Redshift.

• 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, or 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 agile development methodologies such as Scrum or Kanban

• 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

Preferred Education, Experience, & Skills

• 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 AWS services and best practices

Pay Information

Full-Time Salary Range: $64935 - $110390

Please note: This range is based on our market pay structures. However, individual salaries are determined by a variety of factors including, but not limited to: business considerations, local market conditions, and internal equity, as well as candidate qualifications, such as skills, education, and experience.

Employee Benefits: At BAE Systems, we support our employees in all aspects of their life, including their health and financial well-being. Regular employees scheduled to work 20 hours per week are offered: health, dental, and vision insurance; health savings accounts; a 401(k) savings plan; disability coverage; and life and accident insurance. We also have an employee assistance program, a legal plan, and other perks including discounts on things like home, auto, and pet insurance. Our leave programs include paid time off, paid holidays, as well as other types of leave, including paid parental, military, bereavement, and any applicable federal and state sick leave. Employees may participate in the company recognition program to receive monetary or non-monetary recognition awards. Other incentives may be available based on position level and/or job specifics.

Data Engineer

121987BR

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