Pune, Maharashtra, India
Information Technology
Full-Time
ERM
Overview
Job Summary:
We are looking for a skilled and motivated Data Engineer to join our growing data team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support analytics, reporting, and machine learning initiatives. You will work closely with data analysts, data scientists, and software engineers to ensure reliable access to high-quality data across the organization.
Key Responsibilities:
We are looking for a skilled and motivated Data Engineer to join our growing data team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support analytics, reporting, and machine learning initiatives. You will work closely with data analysts, data scientists, and software engineers to ensure reliable access to high-quality data across the organization.
Key Responsibilities:
- Design, develop, and maintain robust and scalable data pipelines and ETL/ELT processes.
- Build and optimize data architectures to support data warehousing, batch processing, and real-time data streaming.
- Collaborate with data scientists, analysts, and other engineers to deliver high-impact data solutions.
- Ensure data quality, consistency, and security across all systems.
- Manage and monitor data workflows to ensure high availability and performance.
- Develop tools and frameworks to automate data ingestion, transformation, and validation.
- Participate in data modeling and architecture discussions for both transactional and analytical systems.
- Maintain documentation of data flows, architecture, and related processes.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field.
- Strong programming skills in Python, Java, or Scala.
- Proficient in SQL and experience working with relational databases (e.g., PostgreSQL, MySQL).
- Experience with big data tools and frameworks (e.g., Hadoop, Spark, Kafka).
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and services like S3, Redshift, BigQuery, or Azure Data Lake.
- Hands-on experience with data pipeline orchestration tools (e.g., Airflow, Luigi).
- Experience with data warehousing and data modeling best practices.
- Experience with CI/CD for data pipelines.
- Knowledge of containerization and orchestration tools like Docker and Kubernetes.
- Experience with real-time data processing technologies (e.g., Apache Flink, Kinesis).
- Familiarity with data governance and security practices.
- Exposure to machine learning pipelines is a plus.
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