We are looking for a skilled Data Engineer with 4–5 years of experience in designing, building, and maintaining data pipelines and large-scale data processing systems. The ideal candidate should be proficient in ETL processes, data warehousing, cloud platforms, and big data technologies. This remote role involves collaborating with data scientists, analysts, and software engineers to deliver scalable, efficient, and high-quality data solutions.
Design, develop, and maintain data pipelines and ETL workflows for structured and unstructured data.
Build and optimize data warehouses, data lakes, and large-scale processing systems.
Work with Python, SQL, Spark, and Hadoop for data transformation and analysis.
Integrate data from multiple sources, ensuring accuracy, consistency, and reliability.
Implement data governance, quality checks, and security best practices.
Deploy and manage data solutions on cloud platforms like AWS, Azure, or GCP.
Collaborate with data scientists, analysts, and product teams to meet business requirements.
Monitor and troubleshoot data pipelines and ensure performance optimization.
Document data flows, processes, and architecture for internal and external stakeholders.
Participate in Agile/Scrum development cycles and support continuous improvement initiatives.
Bachelor’s/Master’s degree in Computer Science, IT, or related field.
4–5 years of professional experience in data engineering or related roles.
Strong proficiency in Python, SQL, Spark, Hadoop.
Experience with ETL tools (Informatica, Talend, or equivalent).
Knowledge of data warehousing concepts and tools (Redshift, Snowflake, BigQuery).
Experience with cloud platforms: AWS, Azure, or GCP.
Strong debugging, troubleshooting, and data optimization skills.
Excellent communication and ability to work independently in remote teams.
Familiarity with Agile/Scrum methodologies.