Job Description (Posting). Evaluating and selecting data warehousing tools for business intelligence, data population, data management, metadata management and warehouse administration for both on-prem and cloud-based engagements Strong working knowledge across the technology stack including ETL, ELT, data analysis, metadata, data quality, audit and design Design, develop, and test in ETL tool environment (GUI/canvas driven tools to create workflows) Experience in design documentation (data mapping, technical specifications, production support, data dictionaries, test cases, etc.) Good exposure and working knowledge of Hadoop eco system services like Hbase, Hive, Spark, Zookeeper, impala, YARN, Kafka. Expertise in setting up HA for HDFS, YARN, Zookeeper, Hadoop cluster performance tuning, automation experience using scripting languages (Shell, Ansible, Python etc.) Proficient in SQL, Hive, PIG, Spark SQL, Shell Scripting, Kafka, Flume, Scoop with large Big Data and Data Warehousing projects with either Java, Python or Scala based Hadoop programming background. Provides technical leadership to a team of data warehouse and business intelligence developers Coordinate with other technology users to design and implement matters of data governance, data harvesting, cloud implementation strategy, privacy, and security Adhere to ETL/Data Warehouse development Best Practices Responsible for Data orchestration, ingestion, ETL and reporting architecture for both on-prem and cloud ( MS Azure/AWS/GCP) Assisting the team with performance tuning for ETL and database processes Skills and attributes for success Proven experience of 8+ years in Data warehousing/ Business Intelligence field Solid hands-on 8+ years of professional experience with creation and implementation of data warehouses on client engagements and helping create enhancements to a data warehouse Strong knowledge of data architecture for staging and reporting schemas ,data models and cutover strategies using industry standard tools and technologies Architecture design and implementation experience with medium to complex on-prem to cloud migrations with any of the major cloud platforms (preferably AWS/Azure/GCP) 8+ years experience in Azure database offerings [ Relational, NoSQL, Datawarehouse ] 8+ years hands-on experience in various Azure/AWS services preferred Azure Data Factory,Kafka, Azure Data Explorer, Storage, Azure Data Lake, Azure Synapse Analytics ,Azure Analysis Services & Databricks, AWS Glue, AWS Redshift, , AWS Data Pipelines, AWS Kinesis/MSK, AWS EMR. Minimum of 8 years of hands-on database design, modeling and integration experience with relational data sources, such as SQL Server databases ,Oracle/MySQL, Azure SQL and Azure Synapse Knowledge and direct experience using business intelligence reporting tools (Power BI, Alteryx, OBIEE, Business Objects, Cognos, Tableau, MicroStrategy, SSAS Cubes etc.) Strong creative instincts related to data analysis and visualization. Aggressive curiosity to learn the business methodology, data model and user personas. Strong understanding of BI and DWH best practices, analysis, visualization, and latest trends. Experience with the software development lifecycle (SDLC) and principles of product development such as installation, upgrade and namespace management Willingness to mentor team members Solid analytical, technical and problem solving skills Excellent written and verbal communication skills Strong project and people management skills with experience in serving global clients Responsibilities, Qualifications, Certifications - External Qualification B Tech, B-Tech Skill (Primary) Data Fabric-Azure-Azure Data Factory (ADF)
