Data Platform Engineer (6+ yrs experience)

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Are you passionate about building and supporting modern data platforms in the cloud? We’re looking for a Sr. Data Platform Engineer who thrives in a hybrid role—60% administration and 40% development/support—to help us scale our data and DataOps infrastructure. You’ll work with cutting-edge technologies like Databricks, Apache Spark, Delta Lake, and AWS CloudOps, Cloud Security, while supporting mission-critical data pipelines and integrations. If you’re a hands-on engineer with strong Python skills, deep AWS experience, and a knack for solving complex data challenges, we want to hear from you.

Are you passionate about building and supporting modern data platforms in the cloud? We’re looking for a Sr. Data Platform Engineer who thrives in a hybrid role—60% administration and 40% development/support—to help us scale our data and DataOps infrastructure. You’ll work with cutting-edge technologies like Databricks, Apache Spark, Delta Lake, and AWS CloudOps, Cloud Security, while supporting mission-critical data pipelines and integrations. If you’re a hands-on engineer with strong Python skills, deep AWS experience, and a knack for solving complex data challenges, we want to hear from you.

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines and integration frameworks.

• Administer and optimize Databricks and Apache Spark environments for data engineering workloads.

• Build and manage data workflows using AWS services such as Lambda, Glue, Redshift, SageMaker, and S3.

• Support and troubleshoot DataOps pipelines, ensuring reliability and performance across environments.

• Automate platform operations using Python, PySpark, and infrastructure-as-code tools.

• Collaborate with cross-functional teams to support data ingestion, transformation, and deployment.

• Provide technical leadership and mentorship to junior developers and third-party teams.

• Create and maintain technical documentation and training materials.

• Troubleshoot recurring issues and implement long-term resolutions.

Minimum Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.

• 5+ years of experience in data engineering or platform administration.

• 3+ years of experience in integration framework development with a strong emphasis on Databricks, AWS, and ETL.

Required Technical Skills

• Strong programming skills in Python and PySpark.

• Expertise in Databricks, Apache Spark, and Delta Lake.

• Proficiency in AWS CloudOps, Cloud Security, including configuration, deployment, and monitoring.

• Strong SQL skills and hands-on experience with Amazon Redshift.

• Experience with ETL development, data transformation, and orchestration tools.

Nice to Have / Working Knowledge

• Kafka for real-time data streaming and integration.

• Fivetran and DBT for data ingestion and transformation.

• Familiarity with DataOps practices and open-source data tooling.

• Experience with integration tools such as Apache Camel and MuleSoft.

• Understanding of RESTful APIs, message queuing, and event-driven architectures

If interested, share your resume at sadiya.mankar@leanitcorp.com