Cloud Data Engineer

Shree Narayani Networking Solutions•Iselin, NJ

1d•Hybrid

About The Position

The Cloud Data Engineer designs, builds, and maintains scalable data pipelines and Azure cloud platforms. The role works with large datasets, optimizes data workflows, and ensures secure and efficient data storage and processing in cloud environments. The position is located in Iselin, New Jersey, and requires working onsite at MetroPark 1–2 days per week. The engagement is listed as 12+ months, at $80 per hour on C2C. Senior candidates are sought; local candidates are strongly preferred, and an in-person final interview may be required.

Requirements

At least 5 years of Python coding experience.
At least 5 years of SQL Server-based development involving large datasets.
At least 5 years of experience developing and deploying ETL pipelines using Databricks and PySpark.
Experience with a cloud data warehouse such as Synapse, BigQuery, Redshift, or Snowflake.
Experience with data warehousing concepts including OLTP, OLAP, dimensions, facts, and data modeling.
Previous experience leading an enterprise-wide Cloud Data Platform migration, with strong architectural and design skills.
Experience with cloud-based data architectures, messaging, and analytics.
Bachelor of Arts degree in an engineering or computer science discipline.
U.S. citizen or green card holder.

Nice To Haves

Experience with Airflow.
Cloud certification(s).
Banking or similar industry experience.
Local candidates are strongly preferred.

Responsibilities

Build and optimize data pipelines for ingesting, transforming, and loading data from various sources while ensuring data quality and integrity.
Design, develop, and deploy Spark programs in Databricks to process and analyze large volumes of data.
Work with Delta Lake, data warehousing, data integration, cloud design, and data modeling.
Work with event-based and streaming technologies to ingest and process data.
Process structured, semi-structured, and unstructured data.
Optimize Databricks jobs for performance and scalability across big data workloads.
Monitor and troubleshoot Databricks jobs, identifying and resolving issues and bottlenecks.
Apply data management, security, and governance best practices within Databricks.
Design and develop enterprise data warehouse solutions.
Write SQL queries and programs, including stored procedures, and reverse-engineer existing processes.
Review code for requirements fit, efficient execution patterns, and compliance with established standards.