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Data Engineer

Roles & Responsibilities

  • Strong hands-on experience with Databricks (Spark/Scala/Python/SQL) and Snowflake
  • Advanced SQL development for ETL and performance tuning
  • Data reconciliation, auditing, and anomaly detection across large datasets
  • Tableau dashboard development and performance optimization

Requirements:

  • Build and maintain scalable data pipelines using Databricks and Snowflake
  • Own the data validation lifecycle (reconciliation, profiling, anomaly detection)
  • Develop and optimize Tableau dashboards for business insights
  • Troubleshoot Spark performance issues and optimize pipeline performance

Job description


Job Title: Data Engineer
Location: Remote (PST/MST)
Pay Rate: $70-80/hr (Negotiable)

Overview:
We are seeking a skilled Data Engineer to design, build, and maintain scalable, auditable data pipelines and deliver reliable data products. The ideal candidate will have strong expertise in Databricks (Spark/Scala/Python/SQL), Snowflake, SQL, and Tableau, with experience in data validation, reconciliation, and performance optimization.

Key Responsibilities:

  • Build and maintain scalable data pipelines using Databricks and Snowflake.

  • Own the data validation lifecycle (reconciliation, profiling, anomaly detection).

  • Develop and optimize Tableau dashboards for business insights.

  • Troubleshoot Spark performance issues and optimize pipeline performance.

  • Collaborate with analysts/scientists to deliver reliable data solutions.

  • Document data lineage, pipeline logic, and metadata.

Required Skills:

  • Strong hands-on experience with Databricks (Spark/Scala/Python/SQL) and Snowflake.

  • Advanced SQL development for ETL and performance tuning.

  • Data reconciliation, auditing, and anomaly detection across large datasets.

  • Tableau dashboard development & performance optimization.

Preferred Skills:

  • Advanced data profiling and anomaly detection techniques.

  • Predictive modeling exposure.

  • Experience translating business needs into data products.

  • Strong communication and documentation skills.


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