Analyst, Data Engineering

Role Overview

The Data Engineering team is responsible for building, maintaining, and optimizing scalable data platforms that enable efficient data ingestion, transformation, orchestration, and consumption across the enterprise. This role focuses on delivering reliable, secure, automated, and scalable data infrastructure supporting business-critical analytics and data products.

What You Will Do

Support the design, implementation, and maintenance of enterprise data platform solutions, develop and deploy data processing workloads using Databricks and Apache Spark, and build and maintain CI/CD deployment pipelines using Harness and other DevOps tools.

Why It Might Be a Fit

The ideal candidate will contribute to platform operations, cloud-based data engineering solutions, CI/CD automation, and production support while partnering with cross-functional teams to ensure a stable and high-performing data ecosystem.

Requirements

• 1-3 years of experience in Data Engineering, Platform Engineering, Site Reliability Engineering (SRE), DevOps, or related technical roles.
• Bachelor’s degree in computer science, Engineering, Information Systems, or a related discipline (or equivalent work experience).
• Hands-on experience with Databricks, Apache Spark, and cloud-based data platforms.
• Experience developing, maintaining, and supporting CI/CD pipelines using Harness, Azure DevOps, GitHub Actions, or similar tools.
• Working knowledge of cloud platforms such as Microsoft Azure, Google Cloud Platform (GCP), or AWS.
• Experience with SQL, Python, PySpark, and data engineering best practices.
• Familiarity with source control tools such as Git/GitHub.
• Basic understanding of Infrastructure as Code (IaC) concepts, preferably Terraform.
• Knowledge of platform monitoring, observability, incident management, and operational support processes.
• Understanding of data governance, security, access management, and platform reliability principles.