Bridgeway Benefit Technologies
SeniorDataEngineer
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“Senior Data Engineer at Bridgeway Benefit Technologies. Skills: Data Engineering, Data Warehousing, ELT, Lakehouse Architecture, Databricks, SQL, Python. Design, develop, and maintain our data warehouse infrastructure. shape our data architecture”
What You'll Achieve.
ensuring secure and efficient data pipelines; enabling advanced analytics across the organization; ensure reliable and scalable execution; ensure platform reliability and trust; ensure compliant handling of sensitive information; cost efficiency and speed; efficient and successful delivery
Industry & Context.
optimizing data systems; resolve data and automation issues; Optimize performance of data workflows and storage for cost efficiency and speed
preference given to East Coast candidates
What They're Looking For.
Must Have
5+ years of hands-on data engineering experience required, 3+ years of experience building and operating data pipelines on a modern lakehouse platform (e. g. , Databricks – Unity Catalog, Delta Live Tables, Asset Bundles), including data modeling, governance, and CI/CD deployment patterns, 3+ years of experience with analytical SQL (ANSI SQL/T-SQL/Spark SQL) and Python for data engineering, including pipeline construction, transformation logic, and automation required, communication skills with the ability to collaborate and influence across engineering, analytics, and business stakeholders required, Bachelor’s degree in Computer Science, Information Technology, or a related field
Nice to Have
Master’s degree preferred, Streaming and ingestion tools, such as Kafka, Kinesis, Event Hubs, Debezium, or Fivetran preferred, GitHub CoPilot knowledge is a plus
What You'll Do.
and maintain our data warehouse infrastructure
shape our data architecture
ensuring secure and efficient data pipelines
enabling advanced analytics across the organization
and maintain a scalable lakehouse architecture
including a medallion (bronze/silver/gold) data model optimized for analytics and AI/ML consumption
and operate ELT pipelines
including workflow orchestration
to ensure reliable and scalable execution
Establish data quality
and observability practices
and proactively monitor and resolve data and automation issues to ensure platform reliability and trust
Ensure data security and compliance
including role-based access controls for security
and governance best practices to ensure compliant handling of sensitive information
Optimize performance of data workflows and storage for cost efficiency and speed
Develop and maintain data pipelines using version control and CI/CD best practices in a collaborative engineering environment
Serve as a trusted expert on organizational data domains
How You'll Work.
Team & Collaboration
working closely with analysts, engineers, and other stakeholders; Partner with engineers, analysts, and stakeholders; mentoring teams; collaboration cross-functionally; Collaborate within an Agile-Scrum framework; ability to collaborate and influence across engineering, analytics, and business stakeholders
Communication Scope
communication skills with the ability to collaborate and influence across engineering, analytics, and business stakeholders required
Process & Methodology
Agile-Scrum framework
Full Job Description
Bridgeway is seeking a Senior Data Engineer to design, develop, and maintain our data warehouse infrastructure. This role involves working closely with analysts, engineers, and other stakeholders to shape our data architecture, ensuring secure and efficient data pipelines, and enabling advanced analytics across the organization. The ideal candidate will have a strong background in data engineering, data warehousing, and ELT processes, along with a passion for optimizing data systems. This is a remote position, with preference given to East Coast candidates. Key Responsibilities: Design, develop, and maintain a scalable lakehouse architecture, including a medallion (bronze/silver/gold) data model optimized for analytics and AI/ML consumption. Design, implement, and operate ELT pipelines, including workflow orchestration, scheduling, and monitoring, to ensure reliable and scalable execution. Establish data quality, testing, and observability practices, and proactively monitor and resolve data and automation issues to ensure platform reliability and trust. Ensure data security and compliance, including role-based access controls for security, encryption, masking, and governance best practices to ensure compliant handling of sensitive information. Optimize performance of data workflows and storage for cost efficiency and speed. Partner with engineers, analysts, and stakeholders to meet data needs; balance cost, performance, simplicity, and time-to-value while mentoring teams and documenting standards. Provide technical leadership and mentorship to team members – guiding best practices, skill development, and collaboration cross-functionally. Enable AI/ML use cases through well-structured data models, feature availability, and platform integrations using tools such as Databricks Vector Search and Model Serving. Develop and maintain data pipelines using version control and CI/CD best practices in a collaborative engineering environment. Collaborate within an Agile-Scrum f
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