Data Engineer: Build Scalable AI-Ready Pipelines

Cogniify; Washington (District of Columbia); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Unlimited PTO

Generous parental leave

Entrepreneurial culture

Open communication

Small, dynamic teams

Medical, Dental and Vision coverage

Disability & Life insurance

Mental health support

Annual bonus program

Employee Stock Purchase Program (ESPP)

Yearly Team building experiences

Mentorship and sponsorship

Job summary

Cogniify is seeking 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, collaborating with analysts, data scientists and engineers to ensure large datasets are accurate and accessible for use.

This hands-on role emphasizes both data engineering and the analytical questions behind the data, with opportunities to contribute to AI-related

Qualifications

• 3 to 6 years of professional experience in data engineering or related data role.
• Strong SQL skills with complex transformations and performance improvements.
• Hands-on experience with a cloud data platform. Snowflake preferred; Databricks/BigQuery/Redshift also relevant.
• Production experience with dbt for transformation, testing and documentation.
• Python knowledge with Pandas or PySpark for data processing.
• Experience scheduling pipelines with Airflow or similar orchestration tools.

Responsibilities

• Build and maintain ETL/ELT pipelines using SQL, Python, dbt and tools like Spark, PySpark or Airflow.
• Ingest data from databases, APIs, SaaS tools and event streams via connectors or custom pipelines.
• Develop tested data models and curated datasets in Snowflake, Databricks, BigQuery or Redshift.
• Collaborate with data scientists to prepare feature datasets for model training and inference.
• Prepare structured business data to support AI search, RAG or Generative AI applications.
• Create dashboards and analyses in Tableau, Looker, Power BI when needed.
• Add data quality checks, monitoring and documentation for reliable data.
• Improve query speed and pipeline cost; use Git, code reviews, CI/CD for safe releases.
• Help manage data access, lineage and PII handling.

Skills

SQL

Python

dbt

ETL/ELT

Apache Spark

Airflow

Snowflake

Databricks

BigQuery

Redshift

Pandas/PySpark

Tools

Airflow

dbt

Spark

PySpark

Tableau/BI

Job description

Cogniify is seeking 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, collaborating with analysts, data scientists and engineers to ensure large datasets are accurate and accessible for use.

This hands-on role emphasizes both data engineering and the analytical questions behind the data, with opportunities to contribute to AI-related