Senior Data Engineer

1) Identifying & driving Digital Transformation initiatives across the Group - Work with business teams to understand the business needs and how emerging technologies can be leveraged. - Ideation, conceptualization & analysis of Digital opportunities across the value chain including manufacturing, supply chain, workplace & customer experience. - Work closely with vendors for planning, executing & supporting Digital projectWorking closely with end users and understand the use case in question. - Design and implement the use case. 2) Creation and implementing cloud-based architecture. - Hands on experience in Python programming and deploying ML models. 3) Creation and implementing of advanced analytics use cases. - Working closely with end users and understand the use case in question. - Design and implement the use case. 4) Collaboration with internal and external teams - Ability to collaborate on a team with infrastructure, BI report development and business analyst resources and clearly communicate solutions to both technical and non-technical team members. Design and implement the use case. - Coordinate with vendors and bridge the gap amongst teams. 5) Create Presentation / Proposal on Value proposition. - Create high quality presentations and value proposition to create stakeholder buy in - Engage with internal stakeholders to evangelize the benefits of Digital technologies and drive cultural change. skill required  Databricks: AWS: S3, DMS, Redshift, EC2, VPC, Lambda, Delta Lake, CloudWatch etc. Bigdata: Databricks, Spark, Glue and Athena Expertise in Lake Formation, Python programming, Spark, Shell scripting Minimum Bachelors degree with 5+ years of experience in designing, building, and maintaining Databricks and AWS data components 3+ years of experience in data component configuration, related roles and access setup Expertise in Python programming Knowledge in all aspects of DevOps (source control, continuous integration, deployments, etc.) Strong hands-on coding skills in Python, processing large-scale data set and developing machine learning models. Experience programming in Python, R, and SQL. Expertise in deploying use cases and AI/ML models in standalone and cloud based systems and services. Knowledge in all aspects of DevOps (source control, continuous integration, deployments, etc.) Comfortable working with DevOps: Jenkins, Bitbucket, CI/CD Hands on ETL development experience, preferably using or SSIS. SQL Server experience required Strong analytical skills to solve and model complex business requirements. Sound understanding of BI Best Practices/Methodologies, relational structures, dimensional data modelling, structured query language (SQL) skills, data warehouse and reporting techniques. Comfortable with creating data models and visualization using Power BI