Lead Data Engineer

Title: Lead Data Engineer

Location: San Francisco, CA/ Remote, USA (Locals )

Duration: 12 months ( Hybrid )

Experience :11+ Years

Visa status :Only H1B, GCEAD,H4EAD

Note : retail client experience , linkedin 2018 below , i94 copy 

Client : Coforge (delivering for Sephora – retail/e-commerce leader)

Description:
We are looking at 8-10 years of software development and deployment experience with at least 7 years of hands-on experience with SQL, Databricks, ADF, Datastage (or other ETL tool), SSAS cubes, Cognos, Tableau, ThoughtSpot and other BI tools Write SQL for processing raw data, kafka ingestions, adf pipelines, data validation and QA Knowledge working with APIs to collect or ingest data Experience with advanced SQL and Python Strong Database knowledge, SQL & No-SQL preferred

Other Responsibilities
Data Architecture Design: Responsible for designing the overall data architecture and data modeling strategies for the BI system. They collaborate with stakeholders to understand business requirements and translate them into a robust and scalable data model. Create logical and physical data models using best practices to ensure high data quality and reduced redundancy.
Data Integration: Will work on integrating data from various sources, such as databases warehouses and external systems. They develop strategies for data extraction, transformation, and loading (ETL) processes to ensure data accuracy, consistency, and availability for reporting and analysis.
BI Tool Selection and Implementation: Evaluate and select appropriate BI tools and technologies based on the organization's needs. Run POC and the implementation and configuration of BI software, including data visualization tools, reporting platforms, and analytics solutions.
Performance Optimization: Monitor and optimize the performance of the BI system to ensure efficient data retrieval, processing, and reporting. They identify and resolve performance bottlenecks by tuning queries, optimizing data structures, and implementing caching mechanisms.
Collaboration and Stakeholder Management: Collaborates with business stakeholders, data analysts, developers, and IT teams to understand their requirements and deliver solutions that meet their needs. They communicate complex technical concepts to non-technical stakeholders and provide guidance on leveraging BI capabilities.
Continuous Improvement: They stay updated with the latest trends, technologies, and best practices in the BI field. They explore opportunities for process improvement, automation, and innovation to enhance the organization's data analytics capabilities.
Data Governance and Security: Needs to establish data governance policies and procedures to ensure data quality, consistency, and security. Define access controls, data privacy measures, and data retention policies to comply with regulatory requirements and protect sensitive information.
Lead, design and implement innovative analytical solution using Tableau, SQL, and other Big Data related technologies
Work with product and engineering team to understand requirements, evaluate new features and architecture to help drive decisions
Build collaborative partnerships with architects, technical leads and key individuals within other functional groups
Perform detailed analysis of business problems and technical environments and use this in designing quality technical solution
Actively participate in code review and test solutions to ensure it meets best practice specifications
Build and foster a high-performance engineering culture, mentor team members and provide team with the tools and motivation to make things happen
Work with stakeholders and cross-functional teams to develop new solutions or enhance existing solution