Lead Data Engineer at Intelliswift - An LTTS Company in Madison, WI
- Company: Intelliswift - An LTTS Company
- Location: Madison, WI
- Posted: Sep 18, 2026
- Type: Full-time
- Salary: $85/hr. to $90/hr.
- Experience: 6+ years
Overview
Pay rate range - $85/hr. to $90/hr. Hybrid - 2-3 Days in Office Job Description Leads an engineering team to meet project deadlines and priorities. Supervises assigned data engineering team members & activities. Ensures the quality, completeness, security, privacy, and integrity of data throughout t…
Job description
- Pay rate range - $85/hr. to $90/hr.
- Hybrid - 2-3 Days in Office
- Job Description
Responsibilities
- Leads an engineering team to meet project deadlines and priorities.
- Supervises assigned data engineering team members & activities.
- Ensures the quality, completeness, security, privacy, and integrity of data throughout the data lifecycle.
- Documents critical workflows and operational support aspects of team's responsibilities
- Develops deep understanding of data sources, granularity, availability, and limitations.
- Provides proactive technical oversight and advice to application architecture and development teams fostering re-use, design for scale, stability, and operational efficiency of data/analytical solutions.
- Creates maintainable, scalable code to load and manipulate data in the data warehouse.
- Facilitates communication upward and across project teams and business stakeholders.
Requirements
- Demonstrated experience providing customer-driven solutions, support or service.
- Must have GCP experience for this positon.
- In-depth knowledge of SQL or NoSQL and experience using a variety of data stores (e.g. RDBMS, analytic database, scalable document stores)
- Extensive hands-on Python programming experience, with an emphasis towards building ETL workflows and data-driven solutions.
- Able to employ design patterns and generalize code to address common use cases.
- Capable of authoring robust, high quality, reusable code and contributing to the division's inventory of libraries.
- Expertise in big data batch computing tools (e.g. Hadoop or Spark), with demonstrated experience developing distributed data processing solutions.
- Knowledge of open source machine learning toolkits, such as sklearn, SparkML, or H2O.
- Solid data understanding and business acumen in the data rich industries like insurance or financial
- Applied knowledge of data modeling principles (e.g. dimensional modeling and star schemas).
- Strong understanding of database internals, such as indexes, binary logging, and transactions.
- Experience using tools for infrastructure-as-code (e.g. Docker, CloudFormation, Terraform, etc.)
- Experience with software engineering tools and workflows (i.e. Jenkins, CI/CD, git).
- Practical experience authoring and consuming web services.
Skills
Required
- GCP
- SQL or NoSQL
- Python
- ETL workflows
- Hadoop or Spark
- Docker, CloudFormation, Terraform
- Jenkins, CI/CD, git
- Web services