Data Engineer

Siro Clinpharm; United States; Remote; USD 37,000 - 73,000; Full time

Job summary

Siro Clinpharm is seeking a Senior Data Engineer to design and optimize scalable data pipelines. This remote role is open to candidates in India with 10+ years of data engineering experience. You will work on batch and streaming pipelines, cloud platforms, and orchestration tools to deliver robust data solutions.

You will mentor junior engineers and collaborate with architects and data scientists to build modern data platforms using Spark, Databricks, and cloud services.

Qualifications

• 10+ years of data engineering experience required.
• Proficiency in Python, SQL and PySpark with Spark ecosystem.
• Experience with ETL/ELT design and scalable pipelines.
• Strong knowledge of cloud data platforms (AWS or Azure).
• Hands-on with Airflow or MWAA and data orchestration.
• Experience with Databricks, Glue and streaming tools like Kafka/Kinesis.

Responsibilities

• Design, develop, and optimize scalable ETL/ELT pipelines.
• Build batch and real-time data processing solutions.
• Develop distributed data processing applications with Spark.
• Create cloud-native data platforms on AWS and/or Azure.
• Implement workflow orchestration using Airflow/MWAA/Glue.
• Build streaming solutions with Kafka/Kinesis/Azure Event Hubs.
• Enhance data quality, observability, and data governance.
• Develop CI/CD pipelines and automate deployments.
• Collaborate with architects, analysts, and data scientists.
• Mentor junior engineers and participate in architecture reviews.

Skills

Python

SQL

PySpark

Apache Spark

ETL/ELT Development

Batch Processing

Streaming Data

CI/CD

Git

Docker

Data Lake / Lakehouse

Data Quality & Governance

Snowflake / Redshift / Synapse

Tools

AWS

Azure

Airflow / MWAA

Databricks

AWS Glue

Kafka / Kinesis

Cloud Platforms

Job description

Greetings !

Role:Senior Data Engineer

Experience:10+ Years

Location: Remote (India)

Key Responsibilities:

• Design, develop, and optimize scalable ETL/ELT pipelines using Python, SQL, and PySpark.
• Build batch and real-time data processing solutions.
• Develop distributed data processing applications using Apache Spark.
• Create and maintain cloud-native data platforms on AWS and/or Azure.
• Implement workflow orchestration using Apache Airflow, AWS MWAA, AWS Glue, and Databricks Workflows.
• Build streaming data solutions using Kafka, Kinesis, or Azure Event Hubs.
• Implement data quality, observability, metadata, and lineage frameworks.
• Develop CI/CD pipelines and automate deployments for data engineering solutions.
• Collaborate with architects, analysts, and data scientists to deliver scalable solutions.
• Mentor junior engineers and participate in architecture reviews.

Mandatory Skills:

• 10+ years of Data Engineering experience
• Python
• SQL
• PySpark
• Apache Spark
• ETL/ELT Development
• Batch & Streaming Data Processing
• AWS and/or Azure
• Apache Airflow / AWS MWAA
• AWS Glue
• Databricks
• CI/CD (GitHub Actions or Azure DevOps)
• Git
• Docker
• Data Lake / Lakehouse Architecture
• Data Quality & Data Governance
• Snowflake or Redshift or Azure Synapse