Data Engineer

CollectiveHealth, Inc.
Plano, United States of America
17 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 169K

Job location

Plano, United States of America

Tech stack

Airflow
Amazon Web Services (AWS)
Data analysis
Business Intelligence
Big Data
Cloud Engineering
Data Infrastructure
ETL
Data Warehousing
Distributed Data Store
Hive
Python
Standard Sql
SQL Databases
Workflow Management Systems
Spark
PySpark
Information Technology
Presto
Terraform
Software Version Control
Data Pipelines
User Administration
Redshift

Job description

  • Data Infrastructure Orchestration - Build and maintain cloud native infrastructure for Data Platform (AWS, Terraform)
  • Data Pipelines - Create new pipelines and improve/maintain existing pipelines using Spark (Python, Pyspark, SQL)
  • Data Modeling - Partner with analytic consumers to design logical and physical schemas, improve existing data models and build new ones
  • Cross-functional Collaboration - Interface with Product, Engineering, Data Science, Analytics/BI, and Operations to understand their data needs, providing both consultative and data engineering solutions for consumers
  • Build data expertise and own data quality across various business domains including healthcare claims and member experience
  • Manage the Business Intelligence development lifecycle, from semantic model development and version control to user administration, ensuring high data quality and consistency from the pipeline through to the visualization layer.
  • Enable fellow developers to "self-service" their data needs
  • Leverage best in industry practices to build the next generation data ecosystem to collect, move, store and analyze data

Requirements

  • BS degree in Computer Science or related technical field, or equivalent practical experience
  • 4+ years proven work experience as a data engineer, working with at least one programming language (e.g. Scala, Python/PySpark) plus SQL expertise
  • 4+ years experience with schema design, dimensional data modeling, and large-scale data warehousing architecture
  • Expertise in building data pipelines through efficient ETL design, implementation and maintenance
  • Background working with distributed data systems such as Spark, Presto, Hive, and Redshift. Experience with BI platform administration and/or schedulers/workflow management tools (e.g. Airflow) a plus
  • Excellent communication skills to collaborate with stakeholders in Engineering, Product, Data Science, Analytics/BI, and Operations

Benefits & conditions

The actual pay rate offered within the range will depend on factors including geographic location, qualifications, experience, and internal equity. In addition to the salary, you will be eligible for 115,000 stock options and benefits like health insurance, 401k, and paid time off. Learn more about our benefits at ;br> Plano, TX Pay Range

$135,080-$168,850 USD

Why Join Us?

  • Mission-driven culture that values innovation, collaboration, and a commitment to excellence in healthcare
  • Impactful projects that shape the future of our organization
  • Opportunities for professional development through internal mobility opportunities, mentorship programs, and courses tailored to your interests
  • Flexible work arrangements and a supportive work-life balance

About the company

At Collective Health, we're transforming how employers and their people engage with their health benefits by seamlessly integrating cutting-edge technology, compassionate service, and world-class user experience design. We deliver a connected healthcare experience for over a quarter million members and 60+ companies across the nation who want the best for their employees. We've got a ton of interesting problems to solve around data pipeline design and implementation, data architecture and modeling, distributed systems, and more. If you're passionate about tackling hard problems while making a real difference in the world, we'd love to talk!

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