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# Data Engineer - 1668

- **Company:** aKube Inc
- **Location:** Santa Monica, CA, United States
- **Experience:** Experienced
- **Salary:** $192,400
- **Contract:** Temporary to permanent
- **Skills:** Airflow, Amazon Elastic Compute Cloud, Amazon S3, Code Review, Continuous Integration, Data Architecture, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Database Queries, DevOps, Distributed Computing Environment, Github, Apache Hive, Identity and Access Management, JSON, SQL Databases, Workflow Management Systems, Parquet, Data Logging, Data Ingestion, Snowflake, Data Lakes, Pyspark, Semi-structured Data, Data Pipelines, Databricks
- **Published:** November 8, 2026
- **Apply:** https://www.dice.com/job-detail/f52ed495-b754-4f98-9088-5252cdda660f

## About the Role

* 4+ years of Data Engineering experience.
 * Strong SQL skills, including complex joins, window functions, and analytical queries.
 * Hands-on production experience with PySpark and/or Spark SQL.
 * Databricks experience, including Delta Lake and Unity Catalog.
 * Strong understanding of ETL/ELT pipelines, data modeling, and distributed processing., * Minimum 4 years of professional Data Engineering experience or equivalent.
 * Experience building production pipelines in Databricks.
 * Strong understanding of Delta Lake, Unity Catalog, Lakehouse architecture, and data governance.
 * Experience with AWS services such as S3, IAM, EC2, Glue, or Lambda.
 * Experience with Apache Airflow or similar orchestration tools.
 * Experience processing JSON, Parquet, CSV, and other semi-structured data.
 * Experience with Git/GitHub, CI/CD, and modern DevOps practices.

Nice to Have:

 * Experience migrating SQL transformations from Snowflake to Databricks.
 * Experience working with marketing acquisition or advertising data.
 * Experience implementing data quality monitoring and pipeline reliability improvements.

## Description

* Develop and maintain ETL/ELT pipelines using Databricks, PySpark, and SQL for marketing acquisition reporting.
 * Migrate existing Snowflake SQL scripts and transformations into Databricks Unity Catalog.
 * Build ingestion pipelines for external marketing vendor data.
 * Perform data parsing, normalization, transformation, and validation.
 * Implement data quality checks, monitoring alerts, and issue resolution workflows.
 * Troubleshoot pipeline failures and improve processing performance.
 * Support SLA monitoring, logging improvements, and pipeline reliability.
 * Collaborate with analytics teams to ensure accurate reporting datasets.
 * Participate in code reviews, documentation, and engineering best practices.