Cloud Data Engineer: Azure Databricks & AWS Expert

Encore Talent Solutions

Brea (CA)

On-site

USD 120,000 - 160,000

Full time

14 days+

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Job summary

Encore Talent Solutions is seeking a Data Engineer to help build and scale its modern cloud data platform in California. The role focuses on designing and developing data pipelines, integrating diverse data sources, and delivering reliable, scalable analytics-ready datasets.

You will collaborate with Data Scientists and business stakeholders to transform raw data into actionable insights, leveraging Azure Databricks, AWS, and Python to support reporting and machine learning initiatives.

Qualifications

Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field.
3+ years of experience in Data Engineering or a similar role.
Hands-on experience with Azure Databricks.
Experience working within AWS.
Strong programming skills in Python.
Advanced SQL development skills.
Experience building scalable ETL/ELT pipelines.
Experience with Git and source control.
Strong understanding of relational databases and data warehousing concepts.

Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using Azure Databricks and PySpark.
Build robust data integration solutions for structured and unstructured data sources.
Design and optimize data models to support reporting, analytics, and machine learning.
Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and scalability.
Implement data quality checks and governance best practices.
Design and maintain cloud-based data storage solutions using Amazon S3.
Configure secure AWS environments for data ingestion from internal and third-party data providers.
Build automated processes for ingesting files into S3 and orchestrating downstream processing.
Work with AWS services including: Amazon S3, AWS Glue, Lambda, IAM, CloudWatch.
Support future cloud-native initiatives utilizing AWS container technologies such as ECS, EKS, or Kubernetes.
Develop internal applications, automation tools, APIs, and utilities using Python.
Build reusable services that streamline business processes and improve operational efficiency.
Collaborate with cross-functional teams to deliver scalable, data-driven solutions.
Partner with Sales, Marketing, Finance, Supply Chain, and Operations teams to understand business requirements.
Support Data Scientists by preparing high-quality datasets for advanced analytics and AI initiatives.
Work closely with IT and business stakeholders to implement enterprise data solutions.