Remote Data Engineer: Pipelines & AI-Ready Data

Dover; California; Hybrid; USD 110,000 - 160,000; Full time

Benefits offered by this job

Unlimited PTO

Generous parental leave

Entrepreneurial culture

Open communication

Small teams

Medical, Dental, Vision

Disability Insurance

Mental health support

Annual bonus

ESPP

Team building

Mentorship & sponsorship

Job summary

Cogniify is seeking a Mid Level Data Engineer to design and maintain reliable data pipelines and analytics datasets for reporting, business decisions and AI initiatives. You will own data from ingestion through transformation and delivery, collaborating with analysts, data scientists and engineers to ensure accuracy and accessibility.

This hands-on role requires strong SQL, experience with cloud platforms (Snowflake preferred) and tooling like dbt, Airflow and Spark to build scalable data

Qualifications

• 3 to 6 years of professional experience in data engineering or related data role.
• Strong SQL skills and experience with complex transformations.
• Experience with a cloud data platform (Snowflake preferred; Databricks/BigQuery/Redshift also relevant).
• Production experience with dbt for transformation, testing and documentation.
• Python and Pandas or PySpark for data processing.
• Experience scheduling pipelines with Airflow, Dagster, Prefect or similar.
• Understanding of data modeling for analyst-friendly datasets.

Responsibilities

• 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).

Skills

SQL skills

Cloud data platform

Snowflake

Databricks

BigQuery

Redshift

dbt

Python

Airflow

Tools

dbt

Job description

Cogniify is seeking a Mid Level Data Engineer to design and maintain reliable data pipelines and analytics datasets for reporting, business decisions and AI initiatives. You will own data from ingestion through transformation and delivery, collaborating with analysts, data scientists and engineers to ensure accuracy and accessibility.

This hands-on role requires strong SQL, experience with cloud platforms (Snowflake preferred) and tooling like dbt, Airflow and Spark to build scalable data