Job
Description
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, Java, Apache Kafka Good to have skills : Google Dataproc Minimum 5 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. You will create data pipelines, ensure data quality, and implement ETL processes to migrate and deploy data across systems. Your typical day will involve designing and developing data solutions, collaborating with teams to ensure data quality, and implementing ETL processes for data migration and deployment. Roles & Responsibilities: Expected to be an SME, collaborate and manage the team to perform. Responsible for team decisions. Engage with multiple teams and contribute on key decisions. Provide solutions to problems for their immediate team and across multiple teams. Design and develop data solutions for data generation, collection, and processing. Create data pipelines to ensure efficient data flow. Implement ETL processes to migrate and deploy data across systems. Ensure data quality and integrity throughout the data solutions. Collaborate with cross-functional teams to gather requirements and understand data needs. Optimize data solutions for performance and scalability. Troubleshoot and resolve data-related issues. Stay up-to-date with the latest trends and technologies in data engineering. Professional & Technical Skills: Must To Have Skills:Proficiency in Apache Spark, Java, and Apache Kafka. Good To Have Skills:Experience with Apache Airflow, Google Dataproc Strong understanding of data engineering principles and best practices. Experience with data modeling and database design. Hands-on experience with data integration and ETL tools. Knowledge of cloud platforms and services, such as AWS or Google Cloud Platform. Experience performing analysis with large datasets in a cloud-based environment, preferably with an understanding of Google's Cloud Platform (GCP) Experience with big data technologies, such as Hadoop and Hive. 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 5 years of experience in Apache Spark. This position is based in Mumbai. A 15 years full-time education is required. Qualifications 15 years full time education
