Machine Learning Data Engineer

Granite Telecommunications


Date: 23 hours ago
City: Quincy, MA
Contract type: Full time
About Us

We’re building software products that rely on data — for insights, automation, and powering customer-facing features. We want to make sure our data is clean, reliable, and usable from the start.

We’re looking for a Data Engineer who can own the pipelines, schemas, and infrastructure that make our data trustworthy and easy to work with. You’ll help us design how data flows through our systems and work closely with engineers, PMs, and data scientists to make it useful.

What You’ll Do

  • Design and maintain data pipelines (batch & streaming) to move data between systems.
  • Build and manage databases, schemas, and data warehouses.
  • Ensure data quality, consistency, and reliability.
  • Work with backend engineers to design event streams, APIs, and logging that generate useful data.
  • Make it easy for product and business teams to query and analyze data.
  • What We’re Looking For
  • Strong SQL skills and experience with relational databases (Postgres, MySQL, etc.).
  • Experience with data warehouses (BigQuery, Snowflake, Redshift, etc.).
  • Hands-on with ETL/ELT pipelines (Airflow, Kafka, or similar).
  • Proficiency in a scripting language (Python preferred).
  • Comfort with cloud services (GCP/AWS).
  • Bonus: experience setting up analytics stacks (Looker, Tableau, Mode, etc.).

A Few Things You Might Work On in the First 3–6 Months

  • Build an ETL pipeline to pull data from production systems into a warehouse for analytics.
  • Design a data model that helps engineers and PMs track key product metrics.
  • Set up monitoring for data quality so we know when pipelines break or data looks suspicious.

Minimum Qualifications

  • 2–5 years years of related experience in data engineering, data analysis, data warehouses, data lakes.
  • Education: Bachelor’s degree
  • Certifications (AWS Big Data, GCP Data Engineer, Snowflake) recommended but optional

This is a foundational role — you’ll define how data is captured, stored, and used across the company. If you want to shape the backbone of our data strategy while working closely with product and engineering, this role is for you.

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