Data Engineer

Job Role: Data Engineer

Job mode: Hybrid

Job type: full time

Job Summary:

Seeking experienced Data Engineers with 6-9 years of experience to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate will have strong expertise in AWS or Azure and big data technologies.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines for ingesting, processing, and transforming large volumes of data.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Optimize data workflows for performance, reliability, and scalability.
• Implement ETL/ELT processes using tools like Apache Spark, Databricks, AWS Glue, or Azure Data Factory.
• Build and manage data lakes, data warehouses, and data marts on AWS (e.g., S3, Redshift) or Azure (e.g., Azure Data Lake, Synapse Analytics).
• Ensure data quality, integrity, and security across all pipelines.
• Automate data pipeline monitoring, alerting, and error handling.
• Stay updated with emerging technologies and best practices in data engineering.

Qualifications:

• 6-9 years of experience in data engineering or related roles.
• Proficiency in programming languages like Python, Scala, or Java.
• Hands-on experience with big data tools (e.g., Apache Spark, Hadoop, Kafka).
• Strong knowledge of SQL and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB).
• Expertise in AWS (e.g., S3, Redshift, Glue, EMR) or Azure (e.g., Azure Data Lake, Synapse Analytics, Databricks).
• Familiarity with data orchestration tools like Apache Airflow or Datafactory or AWS Glue
• Excellent problem-solving and communication skills.