Project Role : Data Engineer
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Apache Spark, Google Dataproc
Good to have skills : Apache Airflow, Apache Kafka
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: As a Data Engineer, you will design, develop, and maintain data solutions for data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across systems. You will play a crucial role in managing and optimizing data infrastructure to support business needs and enable data-driven decision-making. Roles & Responsibilities: - Expected to perform independently and become an SME. - Required active participation/contribution in team discussions. - Contribute in providing solutions to work-related problems. - Design and develop scalable and efficient data pipelines. - Ensure data quality and integrity throughout the data lifecycle. - Implement ETL processes to migrate and deploy data across systems. - Optimize and maintain data infrastructure to support business needs. - Collaborate with cross-functional teams to understand data requirements and deliver solutions. - Stay up-to-date with industry trends and best practices in data engineering. - Additional Responsibility 1: Collaborate with data scientists and analysts to understand their data needs and provide necessary support. - Additional Responsibility 2: Identify and implement automation opportunities to streamline data engineering processes. Professional & Technical Skills: - Must To Have Skills: Proficiency in Java, Apache Spark, Google Dataproc. - Good To Have Skills: Experience with Apache Kafka, Apache Airflow. - Strong understanding of distributed computing principles. - Experience with big data processing frameworks such as Hadoop and Spark. - Proficient in SQL and database technologies. - Familiarity with cloud platforms such as AWS or GCP. Experience performing analysis with large datasets in a cloud-based environment, preferably with an understanding of Google’s Cloud Platform (GCP) - Knowledge of data modeling and database design principles. - Experience with version control systems such as Git. - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. • Strong experience with multiple database models ( SQL, NoSQL, OLTP and OLAP) • Strong experience with Data Streaming Architecture ( Kafka, Spark, Airflow) • Strong knowledge of cloud data platforms and technologies such as GCS, BigQuery, Cloud Composer, Dataproc and other cloud-native offerings • Knowledge of Infrastructure as Code (IaC) and associated tools (Terraform, ansible etc) • Experience pulling data from a variety of data source types including Mainframe EBCDIC), Fixed Length and delimited files, databases (SQL, NoSQL, Time-series) • Comfortable communicating with various stakeholders (technical and non-technical) • GCP Data Engineer Certification is a nice to have Additional Information: - The candidate should have a minimum of 3 years of experience in Apache Spark. - This position is based in Mumbai. - A 15 years full-time education is required.

15 years full time education

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