Data engineer - USA

Posted 6 Hours Ago
Hiring Remotely in United States
Remote
134K-140K Annually
Mid level
Artificial Intelligence • Information Technology • Machine Learning • Consulting
The Role
Build and maintain production ETL/ELT pipelines, data models, and curated datasets for analytics and AI applications. Ingest data from databases, APIs, SaaS tools, and event streams; implement quality checks, monitoring, documentation, governance, and access controls. Collaborate with analysts, data scientists, and ML engineers on reporting, feature datasets, AI search, and RAG applications. Optimize query performance and pipeline costs while using Git, code reviews, and CI/CD for safe releases.
Summary Generated by Built In

The Role

Cogniify is hiring a Mid Level Data Engineer to build reliable data pipelines and analytics datasets for reporting, business decisions and AI initiatives. You will own data work from ingestion through transformation and delivery, working with analysts, data scientists and engineers to make large datasets accurate, accessible and ready for use. This is a hands-on role for someone who enjoys both data engineering and the analytical questions behind the data.

What You Will Do

  • Build and maintain ETL/ELT pipelines using SQL, Python, dbt and tools such as Apache Spark, PySpark or Airflow.

  • Ingest data from databases, APIs, SaaS tools and event streams using connectors or custom pipelines.

  • Develop tested data models and curated datasets in Snowflake, Databricks, BigQuery or Redshift for reporting and self-service analytics.

  • Work with data scientists and ML engineers to prepare feature datasets for model training and inference.

  • Prepare and refresh structured business data that can support AI search, retrieval-augmented generation (RAG) or other Generative AI applications.

  • Build clear dashboards and analyses in Tableau, Looker, Power BI or similar tools when the work calls for it.

  • Add data quality checks, monitoring and documentation so teams can trust the data and identify pipeline issues early.

  • Improve query speed and pipeline cost; use Git, code reviews and CI/CD to release changes safely.

  • Help manage data access, lineage and sensitive information, including personally identifiable information (PII).

What We Are Looking For

  • 3 to 6 years of professional experience in data engineering, analytics engineering or a related data role with production delivery.

  • Strong SQL skills and experience writing complex transformations and improving query performance.

  • Hands-on experience with a cloud data platform. Snowflake is preferred; Databricks, BigQuery or Redshift experience is also relevant.

  • Production experience with dbt for transformation, testing and documentation.

  • Working knowledge of Python and either Pandas or PySpark for data processing.

  • Experience scheduling pipelines with Airflow, Dagster, Prefect or a similar orchestration tool.

  • A good understanding of data modeling and how to build datasets that analysts and business teams can use.

Preferred Experience

  • Apache Spark, Databricks and large-scale data processing.

  • Data quality or observability tools such as Great Expectations, Soda or Monte Carlo.

  • Streaming data with Kafka or Kinesis, or ingestion tools such as Fivetran or Airbyte.

  • Experience preparing data for ML features, AI search, embeddings or RAG applications.

  • Cloud services across AWS, Azure or Google Cloud, and data governance tools such as Unity Catalog or DataHub.

Why Join Cogniify

You will work on data products used for analytics and emerging AI applications, with room to own your pipelines and improve how teams use data. We would like to hear from engineers who care about clean data, dependable systems and useful outcomes.

Perks And Benefits Of Working With Us

  • Unlimited PTO.

  • Please ask us about our very generous parental leave, much above industry standards!.

  • Entrepreneurial culture where pushing limits and taking risks is everyday business.

  • Open communication with management and company leadership.

  • Small, dynamic teams = massive impact.

  • Medical, Dental and Vision coverage for employees.

  • Access to Disability & Life insurance.

  • Mental health and wellbeing support

  • Annual bonus program

  • Employer Stock Purchase Program (ESPP)

  • Yearly Team building experiences

  • Mentorship and sponsorship opportunities

  • Manager resources and support

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other protected characteristic.

Skills Required

  • 3 to 6 years of professional experience in data engineering, analytics engineering, or a related data role with production delivery
  • Strong SQL skills, including complex transformations and query performance optimization
  • Hands-on experience with a cloud data platform, preferably Snowflake or alternatively Databricks, BigQuery, or Redshift
  • Production experience with dbt for transformation, testing, and documentation
  • Working knowledge of Python and either Pandas or PySpark
  • Experience scheduling pipelines with Airflow, Dagster, Prefect, or a similar orchestration tool
  • Understanding of data modeling and building datasets for analysts and business teams
  • Experience with Apache Spark, Databricks, and large-scale data processing
  • Experience with data quality or observability tools such as Great Expectations, Soda, or Monte Carlo
  • Experience with streaming data using Kafka or Kinesis, or ingestion tools such as Fivetran or Airbyte
  • Experience preparing data for ML features, AI search, embeddings, or RAG applications
  • Experience with AWS, Azure, or Google Cloud
  • Experience with data governance tools such as Unity Catalog or DataHub
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The Company
Year Founded: 2025

What We Do

Cogniify is a Bay Area-based AI execution firm that designs, builds, and deploys custom AI systems for Fortune 500 and Global 2000 companies. The company helps enterprises move from AI pilots to industrialized impact and enterprise-scale production, utilizing deep expertise in AI, advanced analytics, data engineering, and domain consulting.

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