Data Engineer Consultant

Indicium AI; Town of Montana (WI); On-site; USD 120,000 - 175,000; Full time

Job summary

Indicium AI is looking for a Data Engineer Consultant to build production-grade data pipelines for major enterprise clients on our US team. You will modernize legacy setups into cloud-native Lakehouses and write code in PySpark, SQL, and Python, deploying with Terraform.

You will collaborate with clients and nearshore squads to deliver in weeks, ensure data quality, lineage, and strict SLAs, and optimize performance and costs. Databricks, dbt, and Airflow expertise are essential for success.

Qualifications

• Hands-On Data Engineering with production code in Python and advanced SQL.
• Databricks Lakehouse experience including PySpark, Unity Catalog and Workflows.
• Infrastructure as Code with Terraform to deploy cloud data infra.

Responsibilities

• Build Lakehouse modernization pipelines converting legacy setups into PySpark, Databricks SQL, and Delta Live Tables.
• Develop modular, tested dbt models and SQL transformations for trusted datasets.
• Automate data infrastructure, enforce governance with Unity Catalog and manage cloud resources with Terraform.
• Build and monitor ELT/ETL workflows using Airflow and Databricks Workflows and ensure data quality and SLAs.
• Collaborate with clients and nearshore teams, participate in standups and code reviews.

Skills

Data engineering

Databricks

dbt

Terraform

Airflow

Tools

Databricks

dbt

Terraform

Python

SQL

Git

Job description

The Opportunity

As a Data Engineer Consultant on our US team, you will build and deploy production-grade data pipelines for major enterprise clients. You will spend your day-to-day writing code, modernizing brittle legacy setups into cloud-native Lakehouses, and making client data clean, fast, and ready for AI applications.

In this role, you will work directly with modern technologies like Databricks, dbt, Python, and Terraform, collaborating with technical clients and our global engineering squads to ship solutions in weeks, not months.

Key Responsibilities

• Build Lakehouse Modernization Pipelines: Convert legacy data setups (Informatica, PL/SQL, legacy data warehouses) into high-performance PySpark , Databricks SQL , and Delta Live Tables (DLT) using Medallion Architecture standards (Bronze, Silver, Gold).
• Data Modeling & Transformation: Write clean, modular, and tested dbt models and advanced SQL to transform raw client data into trusted, business-ready datasets.
• Automate Infrastructure (DataOps): Use Terraform to provision cloud resources (AWS/GCP) programmatically and enforce data governance using Unity Catalog.
• Integrate & Orchestrate: Build and monitor automated ELT/ETL workflows using tools like Apache Airflow and Databricks Workflows, ensuring data quality, lineage, and strict SLA compliance.
• Client Engagement & Collaboration: Embedded directly within client projects, participating in daily standups, code reviews, and working closely with our nearshore delivery squads to deliver on time.
• Troubleshoot & Optimize: Debug failing pipelines, tune complex SQL/Spark queries for performance, and reduce cloud computing costs for our clients.

Qualifications & Requirements

Technical Stack

• Hands-On Data Engineering: Strong background writing production code in Python and advanced SQL.
• Databricks Experience: Hands-on experience building on the Databricks Lakehouse platform (Delta Lake, PySpark, Unity Catalog, Workflows).
• dbt Mastery: Solid experience using dbt for data transformation, testing, and documentation.
• Infrastructure as Code (IaC): Practical experience writing Terraform scripts to deploy AWS or GCP cloud data infrastructure.
• Orchestration & Version Control: Proficient with Git (GitHub/GitLab) for CI/CD workflows and experience with schedulers like Airflow.

Consulting & Delivery Mindset

• Client-Facing Comfort: Ability to communicate technical decisions clearly to client teams and collaborate in a fast-paced consulting environment.
• Problem-Solving Grit: Ability to jump into unfamiliar legacy codebases, figure out how the data flows, and rebuild it cleanly without needing a rigid playbook.
• Quality Focus: Passion for writing testable, documented, and reusable code.

Nice-to-Haves

• Databricks, AWS, or dbt certifications.
• Experience working on migration projects from legacy warehouses (Teradata, Netezza, Snowflake, Redshift) to Databricks.
• Familiarity with streaming tools like Apache Kafka or CDC (Change Data Capture) pipelines.

The anticipated base salary range for this role is $120,000 - $175,000. In addition to base pay, this position may be eligible for an annual discretionary bonus. An individual's final salary offer will be determined based on a variety of factors, including geographic location, experience, specialized skills, and qualifications. This compensation range is subject to updates or modifications at the company's discretion