127 applicants

Company

Symetra · 13 hours ago

Sr. Data Engineer

United States

Full-time

Remote

Mid, Senior Level

$121K/yr - $202K/yr

4+ years exp

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Financial ServicesHealth Insurance

Growth Opportunities

No H1B

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Responsibilities

Deliver on large and complex solution data needs by leading requirements and technical specifications that drive resulting data designs.

Participate in strategic and innovative data design, requirements, walkthroughs, and reviews.

Design and document system integration/configuration as required.

Implement and advance data models and configurations in support of integrating data from source systems and environments to promote Continuous Integration/Continuous Deployment (CI/CD) and CQRS pattern caching.

Research, design, and implement next generation analytics and machine learning platforms.

Build tools, frameworks, APIs, and dashboards to support telemetry and advanced analytics focusing on ways to improve data security, accessibility, reliability, scalability, efficiency and quality.

Lead data governance and guide all data schema/configuration changes.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data EngineeringData PipelinesSnowflakeDBTAWSPythonSQLGitData QualityData GovernanceETL/ELT ToolsWorkflow Orchestration

Required

B.S. in Computer Science, Mathematics, Software/Computer Engineering, Information Systems or Actuarial Science related field.

4+ years of experience in a Data Science, Data Engineering, Analytics Engineering, or Software Engineering capacity.

Strong experience building and maintaining data pipelines, architectures, and workflows using modern tooling and frameworks.

Hands-on experience with Snowflake (or similar data warehousing platforms), including data modeling, schema design, and query optimization for insurance data analytics.

Proficiency with DBT (Data Build Tool) for transforming and modeling data, ensuring data quality, and version control.

Practical knowledge of workflow orchestration tools like Dagster (or similar tools like Airflow) for managing data pipelines, ensuring task dependencies, and orchestrating complex workflows.

Familiarity with Fivetran or similar ETL/ELT tools to automate data ingestion and seamlessly integrate various data sources into the data warehouse.

Experience integrating data from various sources (e.g., APIs, logs, third-party data providers) and building scalable, efficient data ingestion systems.

Extensive experience with AWS (Amazon Web Services), including services such as S3, Lambda, EC2, and RDS. Ability to leverage AWS for data storage, processing, and orchestration.

Strong coding skills in Python for data manipulation, scripting, automation, and creating efficient data workflows.

Advanced knowledge of SQL.

Experience with version control systems like Git for managing code and collaboration within the team.

Familiarity with best practices for ensuring data quality, security, and governance, including creating tests, monitoring data health, and handling sensitive data appropriately.

Excellent ability to collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data needs and deliver tailored solutions.

Strong analytical and problem-solving skills, with a mindset focused on optimization, automation, and improving existing processes.