Data Engineer

SIRO Clinpharm Pvt. Ltd.; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

SIRO Clinpharm Pvt. Ltd. is hiring a Senior Data Engineer for a remote, US-friendly role. You will design and build enterprise-scale data platforms and pipelines, leveraging Python, PySpark, SQL, Spark, Databricks, and Airflow.

The ideal candidate has 10+ years of experience, strong cloud and data engineering skills, and will drive data lake/lakehouse architectures, CI/CD, and streaming processing across AWS/Azure environments.

Qualifications

• 10+ years of experience designing enterprise-scale data platforms.
• Expertise in Python, PySpark, SQL, Spark, Databricks, Airflow.
• Strong AWS/Azure, ETL/ELT, streaming, CI/CD, and data lake architectures.

Responsibilities

• Design and develop scalable ETL/ELT pipelines using Python, SQL, and PySpark.
• Build batch and real-time data processing solutions.
• Develop and optimize Spark-based data platforms on AWS/Azure.
• Implement workflow orchestration using Airflow, MWAA, AWS Glue, and Databricks Workflows.
• Build data quality, lineage, observability, and governance frameworks.
• Implement CI/CD pipelines and DevOps best practices for data platforms.
• Support Data Lakes, Lakehouse architectures, analytics, and AI/ML workloads.
• Collaborate with Data Architects, Data Scientists, and business stakeholders.

Skills

Python

PySpark

SQL

Streaming data processing

CI/CD

Data Lake/Lakehouse architectures

Tools

Apache Spark

Databricks

Airflow

MWAA

AWS Glue

Job description

We're Hiring: Data Engineer | 10+ Years | Remote

Job Description

We are looking for a Senior Data Engineer with 10+ years of experience in designing and building enterprise-scale data platforms and pipelines. The ideal candidate should have strong expertise in Python, PySpark, SQL, Apache Spark, Databricks, Airflow, AWS/Azure, ETL/ELT development, streaming data processing, CI/CD, and Data Lake/Lakehouse architectures.

Key Responsibilities

• Design and develop scalable ETL/ELT pipelines using Python, SQL, and PySpark.
• Build batch and real-time data processing solutions.
• Develop and optimize Spark-based data platforms on AWS/Azure.
• Implement workflow orchestration using Airflow, MWAA, AWS Glue, and Databricks Workflows.
• Build data quality, lineage, observability, and governance frameworks.
• Implement CI/CD pipelines and DevOps best practices for data platforms.
• Support Data Lakes, Lakehouse architectures, analytics, and AI/ML workloads.
• Collaborate with Data Architects, Data Scientists, and business stakeholders.