Data Engineer

• Build and operationalize complex data solutions
• Correct problems and apply data transformations
• Recommend data cleansing and quality solutions
• Design complex data solutions
• Analyze complex data sources to determine value and usage
• Recommend data for inclusion in analytical processes
• Apply data governance, security, and quality practices
• Collaborate across teams to support delivery
• Educate end users on complex data products and analytics environments
• Analyze, assess, and resolve complex data and system defects and incidents
• Test data movement, transformation code, and data components
• Support data pipelines and solutions for artificial intelligence, machine learning, and business intelligence

Data Engineer II, dbt, AWS

• Build and operationalize complex data solutions
• Correct problems and apply transformations
• Recommend data cleansing and quality solutions
• Design complex data solutions
• Analyze complex data sources to determine value and use
• Recommend data for inclusion in analytical processes
• Incorporate data governance, data security, and data quality practices
• Collaborate across teams to support delivery
• Educate end users on complex data products and analytical environments
• Perform data and system analysis, assessment, and resolution for complex defects and incidents
• Test data movement, transformation code, and data components
• Support data solutions for artificial intelligence, machine learning, and business intelligence/insights
• Perform other duties as assigned

Data Engineer II, Python, SQL, Data Bricks, AWS

• Build and operationalize complex data solutions
• Correct problems, apply transformations, and recommend data cleansing and quality solutions
• Design complex data solutions and incorporate new data sources
• Ensure designs are consistent across projects and aligned with data strategies
• Analyze complex data sources to determine value and recommend data for analytical processes
• Apply data governance, data security, and data quality practices
• Act as a data and technology subject matter expert within lines of business
• Support delivery and educate end users on data products and analytics environments
• Analyze, assess, and resolve high-complexity data and system defects and incidents
• Collaborate across teams to support delivery
• Perform other duties as assigned

Senior Data Engineer – Databricks, Snowflake, ETL

• Contribute to modern data engineering teams
• Design, build, and maintain scalable data pipelines and data products
• Develop ETL/ELT processes to ingest, transform, and curate structured and unstructured data
• Ensure data quality, reliability, and performance across data solutions
• Partner with data analysts, data scientists, and product teams to deliver business value
• Develop solutions using cloud-native data platforms, including AWS and GCP exposure for AI capabilities
• Work with Snowflake, BigQuery, and cloud storage solutions
• Support data platform engineering, automation, and pipeline orchestration
• Contribute to data modernization initiatives, including migration to cloud environments
• Prepare and optimize data for AI/ML models
• Apply foundational machine learning workflows and supporting data pipelines
• Leverage AI-assisted tools, including Google Vertex, to enhance productivity and data solutions
• Build awareness of responsible AI, data ethics, and governance practices
• Collaborate with data scientists to operationalize machine learning solutions
• Translate business and analytical needs into scalable data solutions
• Communicate insights and technical concepts to diverse audiences
• Contribute to inclusive, collaborative, product-focused team environments
• Complete a 10-week immersive onboarding and technical training experience
• Join Agile, product-aligned teams supporting enterprise data solutions

Associate Data Engineer – Tech Catalyst Program

• Provide technical leadership for building and enhancing on-premises data warehouse solutions and accelerating migration to AWS, including Amazon Redshift
• Understand and manage stakeholder data needs within a single business vertical
• Design and implement scalable, fault-tolerant data applications on-premises and in AWS to store and process terabytes of upstream data with high availability
• Partner with information architects, platform architects, data scientists and product management on requirements and solution design
• Evaluate business and system processes, enterprise standards and procedures to resolve problems
• Comply with data management policies, standards and procedures
• Lead design, development, testing oversight and production implementation using on-premises RDBMS platforms, Ab Initio, SQL and AWS/Amazon Redshift
• Lead the technical team in delivering data solutions and identifying system and process enhancements
• Collaborate with Product Owners, Product Managers, Program Managers, Scrum Masters and team members in a Scaled Agile framework
• Manage business partner relationships and inter-group planning among technology leadership and peers
• Track data engineering trends and promote recommended practices
• Promote automation and innovative frameworks to avoid redundancy
• Collaborate with data engineering team members to promote Synchrony values and culture
• Perform other duties and special projects as assigned