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Invenergy · 4 months ago

Data Engineer, Enterprise Analytics and A.I.

Chicago, IL

Full-time

Onsite

Mid Level

$90K/yr - $115K/yr

4+ years exp

Invenergy is a leader in energy innovation, focused on providing power generation and storage solutions for a cleaner energy future. The Data Engineer will design, build, and optimize the data infrastructure for enterprise-wide analytics and AI solutions, collaborating with various stakeholders to ensure efficient data access and governance.

ConsultingEnergyEnergy EfficiencyMarketingRenewable Energy

Growth Opportunities

No H1B

Responsibilities

Work with domain experts across the organization to develop data pipelines and ETL processes to ingest, transform, and curate data from various structured and unstructured sources to support the efforts of the Enterprise Business Analysts and Data Scientists

Build and optimize data architecture and processes to support advanced analytics and AI use cases

Build automated workflows to reduce manual work and improve efficiency

Collaborate with data scientists and business analysts to ensure the availability, quality, and usability of data for modeling and reporting

Establish and enforce data governance, security, and privacy standards in collaboration with IT and compliance teams

Evaluate and adopt emerging technologies to enhance Invenergy’s enterprise data platform and analytics capabilities

Effectively communicate technical data concepts to non-technical audiences

Navigate a variety of stakeholders and competing priorities. Right-size solutions based on the need and priority of the task

Qualification

SQLPythonCloud data platformsData architectureMicrosoft Power PlatformData governanceVersion controlCI/CDData securityData meshAgile developmentEnergy sector knowledge

Required

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field

4+ years of experience in data engineering, software engineering, or related roles with demonstrated success in production-level data systems; or an advanced degree with 2+ years of directly relevant experience

Proficiency in SQL and working with relational databases (e.g., PostgreSQL, SQL Server)

Experience with Python or another high-level programming language for scalable data processing and applying software engineering principles

Experience with Microsoft Power Platform and Integration tools

Experience with ingesting data through third party APIs

Experience with cloud data platforms, preferably Azure and Paas Instances

Familiarity with Databricks environment

Strong understanding of modern data architecture and tools

Experience with version control, CI/CD, and infrastructure automation tools

Solid knowledge of data security, quality, and lifecycle management practices

Eligible to work in the United States without the need for employer visa sponsorship now or in the future