Senior Data Engineer

Description

The company is a large infrastructure builder with about 10,000 employees and 18,000 pieces of heavy equipment, and it is ambitious about being the best at what it does.

The role builds the trusted data base for analytics, reporting, operational insight and AI across the company Family of Companies.

You will be a senior individual contributor on the Enterprise Intelligence team, building and running lakehouse pipelines and reusable data products.

You will help set engineering standards that turn raw source data into durable enterprise assets, helping a small team scale through shared patterns, automation and observability.

This is a hands-on role where you own work from design through production support, and you will mentor engineers and lead technical direction within delivery work.

You will report to the IT Manager, Data Platform & Engineering and sit within the Information Technology organization.

Responsibilities

• Build and maintain batch, streaming and event-driven pipelines that move data from enterprise source systems into the lakehouse.
• Write transformation logic and scheduled workflows that convert raw data into governed, usable datasets.
• Design and tune data assets for analytics, operational reporting, downstream applications and AI use.
• Add validation checks, monitoring and alerts to pipelines and data products so problems are caught and fixed fast.
• Improve performance, scalability and cost of pipeline, storage and compute workloads.
• Create engineering standards and reference architectures so a small team can grow without losing quality.
• Lead technical design reviews and mentor engineers through pairing, code reviews and technical guidance.

Requirements

• A bachelor's degree in computer science, information systems, engineering or a related technical field, or equivalent hands-on experience.
• At least 5 years of production experience in data, platform, analytics or software engineering.
• Proven experience building and running large-scale cloud data platforms such as Databricks, Snowflake, Microsoft Fabric or BigQuery.
• Strong skills in SQL, Python and Spark or similar distributed processing frameworks, plus version control, automated testing, CI/CD and streaming ingestion.
• Experience building observable pipelines with monitoring, lineage and data quality controls that meet enterprise governance, privacy and security rules.
• Equal opportunity employer; applicants are considered without regard to race, age, sex, marital status, sexual orientation, gender identity, veteran status or disability.