Technical Lead - AWS Data

Experience : 7-12 years Desirable Skills : • AWS Data & Analytics Specialty Certification • AWS Solution Architect Associate Certification • Databricks Certification Primary Skills : • Masters / Bachelors Degree in Computer Science, Information Technology or other relevant fields. • Minimum 7+ Years of Mandatory experience in Advance Data & Analytics Architecture, ETL, Data Engineering solutions using the following Skills, tools and technologies: • AWS Data & Analytics Services: Athena, Glue, EMR, DynamoDB, Redshift, Kinesis, Lambda • Databricks Lakehouse Platform • PySpark, Spark SQL, Spark Streaming • Experience with Apache Kafka / Nifi for use with streaming data / event-based data • Experience with any NoSQL Database • 3+ year of coding experience with modern programming or scripting language (Python). • Expert-level skills in writing and optimizing SQL. • Experience operating very large data warehouses or data lakes/ data platform. • Show efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data. • Experience of working in Agile delivery • Sound knowledge of distributed systems and data architecture (lambda)- design and implement batch and stream data processing pipelines, knows how to optimize the distribution, partitioning, and MPP of high-level data structures • Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, and testing. • Excellent business and communication skills to work with business owners to understand data requirements. Responsibilities : • You will be responsible to understand the client requirement and architect robust data platform on AWS cloud technologies and Databricks. • You will be responsible for identifying and creating reusable data solutions (accelerators, MVP) • You will be responsible for creating reusable components for rapid development of data platform • Work closely with the Product Owners and stake holders to design the Technical Architecture for data platform to meet the requirements of the proposed solution. • Work with the leadership to set the standards for software engineering practices within the Data engineering team and support across other disciplines • Play an active role in leading team meetings and workshops with clients. • Delivering and presenting proofs of concept to of key technology components to project stakeholders. • Educate clients on Cloud technologies and influence direction of the solution. • Choose and use the right analytical libraries, programming languages, and frameworks for each task. • Help us to shape the next generation of our products. • Explore and learn the latest AWS Data & Analytics and Databricks Platform features /technologies to provide new capabilities and increase efficiency. • Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services in combination with 3rd parties – Databricks, Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda,Glue, Athena. • Analyze, re-architect and re-platform, migrate on-premise data warehouses to data platforms on AWS cloud using AWS or 3rd party services. • Design and build production data pipelines from ingestion to consumption within a big data architecture, using Python,PySpark, Databricks. • Design and implement data engineering, ingestion and curation functions on AWS cloud using AWS native or custom programming. • Perform detail assessments of current state data platforms and create an appropriate transition path to AWS cloud & Databricks. • Build and deliver high quality data architecture to support business analyst, data scientists, and customer reporting needs. Key Scanners : ETL,AWS,Data Bricks,AWS Glue,Amazon Redshift,AWS PaaS