ETL Developer

Overview

On Site
Depends on Experience
Full Time

Skills

ETL
Snowflake
Data Engineer
Qlik Replicate
SQL
data integration
API
data modeling
normalization
YugabyteDB

Job Details

Position -ETL Developer

Location -Berkeley Heights, NJ (Fully Onsite)

Full-time / W2 - with Infinite Computer Solutions

Position Summary:

We are seeking a skilled ETL Developer to design, build, and maintain robust data pipelines for structured and semi-structured data across real-time, near-real-time, and batch workloads. The ideal candidate will be hands-on with modern ETL tools and data platforms, with strong experience in Snowflake, data integration, and data quality management.

Required Skillset & Experience:

  • 7+ years of experience as an ETL Developer or Data Engineer.
  • Proven expertise in ETL/ELT pipeline design for structured and semi-structured data.
  • Hands-on experience with Qlik Replicate or equivalent real-time replication tools.
  • Strong proficiency with Snowflake (data ingestion, SQL, performance tuning).
  • Solid understanding of data integration from APIs and external data sources.
  • Experience in data modeling, normalization, and relational database design.
  • Knowledge of data governance, quality frameworks, and best practices.
  • Proficient in Python and Java scripting for ETL logic and automation.
  • Familiarity with CI/CD tools such as Git, Jenkins, or Azure DevOps.
  • Experience working with distributed databases like YugabyteDB.

Key Responsibilities:

  • Design, develop, and maintain efficient ETL/ELT pipelines to ingest, transform, and load data from a variety of sources.
  • Implement real-time and near-real-time replication using tools like Qlik Replicate or similar technologies.
  • Work extensively with Snowflake, including data loading, transformation (SQL and scripting), and performance tuning.
  • Integrate and manage multiple data sources, including flat files, databases, and third-party APIs.
  • Develop and optimize data models, ensure proper data normalization, and maintain high-quality data structures.
  • Ensure data governance, data lineage, and security compliance throughout the data lifecycle.
  • Implement and support CI/CD pipelines for automated data pipeline deployments and testing.
  • Write efficient Python and Java scripts for data manipulation, transformation, and automation tasks.
  • Collaborate with DevOps and cloud teams to build scalable, fault-tolerant data workflows.
  • Utilize and manage distributed SQL databases such as YugabyteDB.
  • Perform data validation, error handling, and implement logging and monitoring for pipeline health and SLA compliance.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.