Senior Data Engineer

Intelliswift - An LTTS Company; Madison (WI); On-site; USD 115,000 - 155,000; Full time

Job summary

Intelliswift - An LTTS Company seeks a data engineering lead to drive data solutions across the lifecycle. You will guide architecture, develop scalable ETL, and mentor teams to deliver robust data pipelines.

The role requires deep experience with GCP, Python-based ETL, and modern data stores, with emphasis on data quality, security, and scalable design. Collaboration with stakeholders is essential to success.

Qualifications

• Customer-driven data solutions experience.
• Proficient with SQL or NoSQL and diverse data stores.
• Extensive Python ETL development for data workflows.
• Experience with big data batch tooling (Hadoop or Spark).
• Knowledge of ML toolkits (scikit-learn/SparkML/H2O).
• Strong data modeling principles and database internals understanding.
• Experience with CI/CD tools and version control (Jenkins, Git).

Responsibilities

• Leads an engineering team to meet project deadlines and priorities.
• Ensures data quality, security, privacy, and integrity across data lifecycles.
• Documents critical workflows and operational support aspects of team responsibilities.
• Develops deep understanding of data sources, granularity, availability, and limits.
• Provides proactive technical oversight to data architecture and development teams.
• Creates maintainable, scalable code to load/manipulate data in the data warehouse.
• Facilitates communication across project teams and stakeholders.

Skills

GCP

SQL

Python

ETL

Big data

Hadoop

Spark

CI/CD

Data modeling

Tools

Docker

CloudFormation

Terraform

Job description

Leads an engineering team to meet project deadlines and priorities.

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.

Specialized Knowledge & Skills 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.