Senior Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and construct the transformation layer within Snowflake (raw → staging → conformed → marts) as the governed foundation for all subsequent reporting and AI/ML applications.

• Transition existing SQL views to dbt-style versioned, tested models with comprehensive lineage.

• Establish conformed dimensions and operational facts across Novanta’s multi-ERP landscape utilizing Kimball dimensional modeling principles.

• Set standards for modeling, testing, naming, documentation, and CI/CD for the team, including Git workflows, code review methodologies, dbt project organization, model contracts, and release management.

• Collaborate with report owners and stakeholders to ensure semantic consistency and reduce disruption during the transition from previous datasets.

• Execute data quality testing, observability, and lineage, and work alongside IT Audit on SOX-relevant controls for financial data processes.

• Design models with downstream AI/ML and agent consumption in consideration, which includes documented model contracts and stable surrogate keys.

• Mentor and guide the team by establishing standards and supporting junior members.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related discipline; equivalent professional experience will be considered.

• Over 7 years of experience in data engineering or analytics engineering, with at least 4 years dedicated to building production workloads on a cloud data warehouse (Snowflake is highly preferred; BigQuery, Databricks, or Redshift will be considered with equivalent expertise).

• Proficient in SQL—window functions, performance optimization, and incremental load patterns at scale.

• At least 3 years of experience with dbt in production (or a comparable transformation framework), including macros, both generic and singular tests, snapshots, incremental strategies, exposures, and documentation.

• Practical experience with Kimball dimensional modeling—star schemas, conformed dimensions, fact grain decisions, surrogate keys, and SCD Type 1 and Type 2 patterns.

• Production-level experience with at least one ingestion tool (Fivetran, Airbyte, Informatica, or Matillion) and one orchestrator (dbt Cloud, Airflow, Dagster, or Azure Data Factory).

• Proficient in Git and CI/CD for data (GitHub Actions, Azure DevOps Pipelines, or GitLab CI), encompassing code review and release management practices.

• Competent in Python for data tooling—dbt macros, automation scripts, data quality frameworks, and lightweight API integration.

• Direct experience in modeling data sourced from at least one major enterprise ERP (Oracle, SAP S/4HANA, SAP ECC, Microsoft Dynamics, or similar).

• Strong written communication skills—capable of drafting standards, runbooks, and documentation that non-engineers can comprehend.

• A self-motivated individual who excels in a fast-paced, multi-ERP environment with minimal supervision.

🏝️ Benefits

• Comprehensive medical benefits

• Financial benefits

• Additional benefits to enhance quality of life