Data Engineer

Resultant; United States; On-site; USD 100,000 - 150,000; Full time

Job summary

Resultant is seeking a full-time Data Engineer to design, build, and optimize Lakehouse-based data platforms for diverse clients. You will transform disconnected data into governed, analytics-ready assets while collaborating with solution architects and data scientists.

Responsibilities include designing ETL/ELT pipelines on Databricks with PySpark, implementing Medallion patterns, and ensuring data quality across the lifecycle. 2+ years of Databricks experience and strong SQL are required.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
• 2+ years hands-on experience with data engineering on Databricks.
• Strong proficiency in PySpark and Spark SQL.
• Experience with Delta Lake fundamentals and SQL across relational platforms.
• Familiarity with at least one cloud platform (Azure, AWS, or GCP) and their data services.

Responsibilities

• Design and optimize scalable ETL/ELT pipelines on Databricks using PySpark and Spark SQL
• Implement Medallion architecture patterns and maintain data quality checks throughout the data lifecycle
• Collaborate with clients to gather requirements and translate technical solutions into business impact

Skills

PySpark

Spark SQL

SQL

Education

Bachelor's degree in Computer Science, Engineering, Data Science, or related field

Tools

Delta Lake

Azure

AWS

GCP

Job description

Joining the Databricks practice, the full-time Data Engineer will design, build, and optimize Lakehouse-based data platforms for diverse clients, transforming disconnected data into governed, analytics-ready assets while collaborating with solution architects and data scientists.

Key responsibilities

• Design and optimize scalable ETL/ELT pipelines on Databricks using PySpark and Spark SQL
• Implement Medallion architecture patterns and maintain data quality checks throughout the data lifecycle
• Collaborate with clients to gather requirements and translate technical solutions into business impact

Required qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
• 2+ years of hands‑on experience with data engineering, specifically on the Databricks platform
• Strong proficiency in PySpark and Spark SQL
• Experience with Delta Lake fundamentals and solid SQL skills across various relational platforms
• Familiarity with at least one major cloud platform (Azure, AWS, or GCP) and its data services