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Data Ideology

Enterprise data strategy and platform implementation

Lead Data Engineer - Snowflake

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listed

About the Job

Requirements

  • At least 7 years of experience in data engineering, data warehousing, or data architecture.
  • At least 3 years of hands-on Snowflake experience, including performance tuning, data sharing, Snowpark, or Snowpipe.
  • Strong SQL and Python skills, with production experience using dbt.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP and modern data tooling such as Airflow, Fivetran, Power BI, Looker, or Informatica.
  • Prior experience in a consulting or client-facing delivery role.

Responsibilities

  • Design and build scalable, secure, and cost-effective data solutions in Snowflake.
  • Develop and optimize data pipelines using tools such as dbt, Python, CloverDX, and cloud-native services.
  • Participate in client discovery sessions to gather requirements and translate them into solution designs and project plans.
  • Collaborate with engagement managers and account teams to help scope work and provide technical input for Statements of Work.
  • Serve as a Snowflake subject matter expert, guiding best practices in performance tuning, cost optimization, access control, and workload management.
  • Lead modernization and migration initiatives to move clients from legacy systems into Snowflake.
  • Integrate Snowflake with business intelligence tools, governance platforms, and artificial intelligence/machine learning frameworks.
  • Contribute to internal accelerators, frameworks, and proofs of concept.
  • Mentor junior engineers and support knowledge sharing across the team.

Desired Qualifications

  • SnowPro Certification.

About the Company

Data Ideology

Enterprise data strategy and platform implementation

Data Ideology helps large organizations turn chaotic data into a competitive advantage with data strategy, AI readiness, modern data platforms, analytics optimization, governance, and fractional data teams. They start with a strategy and readiness assessment, then build or upgrade a data platform, optimize analytics tools, establish governance, and supply experienced data teams to execute. They differentiate themselves by offering boutique, executive-level data professionals delivering big-firm caliber solutions without high rates or junior staff. Their goal is to stop data chaos and help clients monetize information through faster, data-driven decisions and measurable ROI.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Pittsburgh, PA
Founded
2017

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