Job Description
As a Senior Data Engineer, you will play a crucial role in designing, developing, and maintaining robust data infrastructure and solutions that enable efficient and reliable data processing, storage, and analysis.
You will work closely with cross-functional teams to understand business requirements and translate them into scalable and performant data pipelines and systems.
Key Responsibilities:
1. Design, build, and optimize data pipelines and ETL workflows to extract, transform, and load data from various sources into data warehouses or data lakes.
2. Develop and maintain scalable and high-performance data processing systems using technologies like Apache Spark, Hadoop, or cloud-based solutions (AWS Glue, Azure Data Factory).
3. Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and provide data engineering support for their analytics and modeling needs.
4. Ensure data quality and integrity by implementing data validation, cleansing and transformation processes.
5. Design and implement efficient data storage and retrieval mechanisms, considering factors like data volume, velocity, and variety.
6. Work on data modeling and schema design to support analytical reporting and data visualization needs.
Required Skills and Qualifications:
- Extensive experience in data engineering and working with large-scale datasets.
- Proficiency in programming languages such as Python, Java, or Scala.
- Strong knowledge of distributed computing frameworks like Apache Spark.
- Experience with data pipeline and ETL tools like Apache Airflow, Informatica, or Talend.
- Proficiency in SQL and experience working with relational databases.
- Familiarity with data warehousing concepts and technologies (e.g., Snowflake, Redshift, Big Query).
- Knowledge of cloud platforms and services (AWS, Azure, or Google Cloud) for data engineering.
- Understanding of data modeling techniques and schema design principles.
- Strong problem-solving and analytical skills
You will work closely with cross-functional teams to understand business requirements and translate them into scalable and performant data pipelines and systems.
Key Responsibilities:
1. Design, build, and optimize data pipelines and ETL workflows to extract, transform, and load data from various sources into data warehouses or data lakes.
2. Develop and maintain scalable and high-performance data processing systems using technologies like Apache Spark, Hadoop, or cloud-based solutions (AWS Glue, Azure Data Factory).
3. Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and provide data engineering support for their analytics and modeling needs.
4. Ensure data quality and integrity by implementing data validation, cleansing and transformation processes.
5. Design and implement efficient data storage and retrieval mechanisms, considering factors like data volume, velocity, and variety.
6. Work on data modeling and schema design to support analytical reporting and data visualization needs.
Required Skills and Qualifications:
- Extensive experience in data engineering and working with large-scale datasets.
- Proficiency in programming languages such as Python, Java, or Scala.
- Strong knowledge of distributed computing frameworks like Apache Spark.
- Experience with data pipeline and ETL tools like Apache Airflow, Informatica, or Talend.
- Proficiency in SQL and experience working with relational databases.
- Familiarity with data warehousing concepts and technologies (e.g., Snowflake, Redshift, Big Query).
- Knowledge of cloud platforms and services (AWS, Azure, or Google Cloud) for data engineering.
- Understanding of data modeling techniques and schema design principles.
- Strong problem-solving and analytical skills
💡 Quick Summary
Seeking a career-building opportunity? The Data Engineer position is now open for candidates interested in the Remote Jobs sector. This role in New Delhi offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Remote Jobs is a plus.
