Data Engineering Team Lead
3 days ago
About the Role
">We are seeking a highly skilled Data Engineering Team Lead to lead our data engineering team in designing and implementing scalable data solutions on cloud platforms. As a key member of our team, you will be responsible for leading multiple data engagements on GCP Cloud for data lakes, data engineering, data migration, data warehouse, and business intelligence.
">Your Key Responsibilities
">- ">
- Lead multiple data engagements on GCP Cloud for data lakes, data engineering, data migration, data warehouse, and business intelligence.">
- Interface with multiple stakeholders within IT and business to understand the data requirements.">
- Take complete responsibility for the successful delivery of all allocated projects on the parameters of Schedule, Quality, and Customer Satisfaction.">
- Responsible for design and development of distributed, high volume multi-thread batch, real-time, and event processing systems.">
- Implement processes and systems to validate data, and monitor data quality, ensure production data is always accurate and available for key stakeholders and business processes that depend on it.">
- Work with the Pre-Sales team on RFPs, and RFIs and help them by creating solutions for data.">
- Mentor Young Talent within the Team and define and track their growth parameters.">
- Contribute to building Assets and Accelerators.">
Requirements
">To succeed in this role, you should have:
">- ">
- A minimum of 6-9 years of experience in building and managing Data Lakes, Data Warehouse, Data Integration, Data Migration and Business Intelligence/Artificial Intelligence solutions on Cloud (GCP/AWS/Azure).">
- Ability to understand business requirements, translate them into functional and non-functional areas, and define non-functional boundaries in terms of Availability, Scalability, Performance, Security, Resilience etc.">
- Experience in architecting, designing, and implementing end-to-end data pipelines and data integration solutions for varied structured and unstructured data sources and targets.">
- Experience of having worked in distributed computing and enterprise environments like Hadoop, GCP/AWS/Azure Cloud.">
- Well-versed with various Data Integration, and ETL technologies on Cloud like Spark, Pyspark/Scala, Dataflow, DataProc, EMR, etc. on various Cloud.">
- Experience of having worked with traditional ETL tools like Informatica/DataStage/OWB/Talend, etc.">
- Deep knowledge of one or more Cloud and On-Premise Databases like Cloud SQL, Cloud Spanner, Big Table, RDS, Aurora, DynamoDB, Oracle, Teradata, MySQL, DB2, SQL Server, etc.">
- Exposure to any of the No-SQL databases like Mongo dB, CouchDB, Cassandra, Graph dB, etc.">
- Experience in architecting and designing scalable data warehouse solutions on cloud on Big Query or Redshift.">
- Experience in having worked on one or more data integration, storage, and data pipeline toolsets like S3, Cloud Storage, Athena, Glue, Sqoop, Flume, Hive, Kafka, Pub-Sub, Kinesis, Dataflow, DataProc, Airflow, Composer, Spark SQL, Presto, EMRFS, etc.">
- Preferred experience of having worked on Machine Learning Frameworks like TensorFlow, Pytorch, etc.">
- Good understanding of Cloud solutions for Iaas, PaaS, SaaS, Containers and Microservices Architecture and Design.">
- Ability to compare products and tools across technology stacks on Google, AWS, and Azure Cloud.">
- Good understanding of BI Reposting and Dashboarding and one or more toolsets associated with it like Looker, Tableau, Power BI, SAP BO, Cognos, Superset, etc.">
- Understanding of Security features and Policies in one or more Cloud environments like GCP/AWS/Azure.">
- Experience working in business transformation projects for the movement of On-Premise data solutions to Clouds like GCP/AWS/Azure.">
Salary Information
">The salary for this position is estimated to be around ₹25,00,000 - ₹40,00,000 per annum based on industry standards and market conditions.
">Other Benefits
">In addition to a competitive salary, we offer a range of benefits including health insurance, retirement plans, paid time off, and opportunities for professional growth and development.
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