Senior Data Engineer

Novanta Inc.

Senior Data Engineer responsible for designing and building Snowflake transformation layer. Focus on data engineering and analytics in healthcare and advanced manufacturing industries.

Posted 7/30/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $101,100 - $161,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Data Engineering with a focus on Snowflake, SQL, and dbt for building and managing data transformation layers. Proficient in Kimball dimensional modeling and experienced in implementing data quality controls and CI/CD practices.

Highest-signal resume keywords

Snowflake Data WarehouseExpert SQLDbt Transformation FrameworkKimball Dimensional ModelingData Quality Testing

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data EngineeringSQLDbtKimball ModelingPythonData Quality FrameworksIncremental Load PatternsSurrogate KeysPerformance TuningCI/CD Standards

Soft Skills

Strong Written CommunicationMentoringSelf-Starter

Tools & Technologies

FivetranAirbyteInformaticaMatillionDbt CloudAirflowDagsterAzure Data FactoryGitHub ActionsAzure DevOps Pipelines

Industry Keywords

Multi-ERP EnvironmentSOX ControlsData LineageSemantic EquivalenceProduction Workloads

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAzureBigQueryCloudERPInformaticaMatillionOraclePythonSQL

About the role

Key responsibilities & impact

Design and build the transformation layer in Snowflake (raw → staging → conformed → marts) as the governed foundation for all downstream reporting and AI/ML use cases.
Migrate existing SQL views to dbt-style versioned, tested models with full lineage.
Define conformed dimensions and operational facts across Novanta’s multi-ERP environment using Kimball dimensional modeling principles.
Set modeling, testing, naming, documentation, and CI/CD standards for the team, including Git workflows, code review practices, dbt project structure, model contracts, and release management.
Partner with report owners and stakeholders to validate semantic equivalence and minimize disruption during cutover from past datasets.
Implement data quality testing, observability, and lineage, and partner with IT Audit on SOX-relevant controls for financial data flows.
Design models with downstream AI/ML and agent consumption in mind, including documented model contracts and stable surrogate keys.
Mentor and lead the team by setting standards and guiding junior members.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field; equivalent professional experience considered.
7+ years in data engineering or analytics engineering, including 4+ years building production workloads on a cloud data warehouse (Snowflake strongly preferred; BigQuery, Databricks, or Redshift considered with equivalent depth).
Expert SQL—window functions, performance tuning, and incremental load patterns at scale.
3+ years of dbt in production (or equivalent transformation framework), including macros, generic and singular tests, snapshots, incremental strategies, exposures, and documentation.
Hands-on experience with Kimball dimensional modeling—star schemas, conformed dimensions, fact grain decisions, surrogate keys, and SCD Type 1 and Type 2 patterns.
Production experience with at least one ingestion tool (Fivetran, Airbyte, Informatica, or Matillion) and one orchestrator (dbt Cloud, Airflow, Dagster, or Azure Data Factory).
Hands-on Git and CI/CD for data (GitHub Actions, Azure DevOps Pipelines, or GitLab CI), including code review and release management practices.
Proficient in Python for data tooling—dbt macros, automation scripts, data quality frameworks, and lightweight API integration.
Direct experience modeling data sourced from at least one major enterprise ERP (Oracle, SAP S/4HANA, SAP ECC, Microsoft Dynamics, or comparable).
Strong written communication—able to author standards, runbooks, and documentation that non-engineers can follow.
Self-starter thriving in a fast-paced, multi-ERP environment with minimal supervision.

Benefits

Comp & perks

full range of medical benefits
financial benefits
other benefits to improve quality of life