About the role
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.
Originally posted on Himalayas