Job Title: DataOps Engineer

Experience: 7+ Years

Role Overview

We are looking for a DataOps Engineer to build and maintain scalable data pipelines and ensure smooth, reliable data operations. The role involves working closely with data engineering, analytics, and DevOps teams to enable efficient data workflows.

Key Responsibilities

Develop and maintain ETL/ELT data pipelines

Implement DataOps practices (CI/CD) for data workflows

Monitor and optimize pipeline performance and reliability

Ensure data quality, governance, and security

Collaborate with cross-functional teams

Mandatory Skills

Strong Python and SQL

Experience with ETL pipelines

Hands-on with Airflow or similar orchestration tools

Experience with Cloud (AWS/Azure/GCP)

Knowledge of Data Warehousing (Snowflake/Redshift/BigQuery)

Understanding of CI/CD and version control (Git)

Good to Have

Databricks and Spark

Docker / Kubernetes

Kafka or streaming tools

175k

Data Engineer – Job Description

We are looking for a Data Engineer to design, build,



and maintain scalable data pipelines that support analytics and data products. The role involves working closely with data scientists and engineering teams to ensure reliable and effective data infrastructure.

Key Responsibilities

Design and develop data pipelines (batch and streaming) using Databricks and PySpark.

Write optimized PySpark code to process large datasets.

Build and manage CI/CD pipelines for data workflows using GitHub / GitHub Actions / Azure DevOps.

Implement data validation and data quality checks.

Monitor pipelines using logging, alerting, and observability tools.

Collaborate with cross-functional teams and document data pipeline architecture.

Mandatory Skills

7 years of Data Engineering experience

Databricks

PySpark

End-to-end Data Pipeline Development (Batch / Streaming)

GitHub (branching, pull requests, code reviews)

CI/CD for Data Pipelines (GitHub Actions / Azure DevOps)

Data Validation / Data Quality Framewor

📌 Backend Developer (India)
🏢 Sparix Global
📍 India