Team Lead BI Data Warehousing

The Responsibilities:

• Participate in analyzing the use cases and requirements from the business stakeholders and product teams for various business KPIs, reporting, and dashboarding needs.
• Participate in design discussions and brainstorm/propose the most intuitive ways to analyze and visualize such KPIs and reporting needs
• Work closely with the analytics teams and business teams to derive actionable insights, helping the organization in achieving its' strategic goals.
• Involve in high levels of interaction with the integrated analytics team, including data engineers, Bl developers and data architects.
• Partner with Product Management to ensure data design, engineering and implementation is in accordance with design intention and meets business needs.
• Has expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation.
• Create technical design documentation in adherence to business, source system, target system, and solution architecture requirements.
• Work with technology leadership to identify, implement new technologies and techniques that can improve our overall platform performance and ultimate customer experience.
  Is able to communicate complex technical concepts to both technical and non technical audience.
• Plays a key role in driving ideation around the modeling process and developing models. Can conceptualize and drive re-iteration and fine tuning of models.
• Contribute to knowledge building and sharing by researching best practices, documenting solutions, and continuously iterating on new ways to solve problems and mentors junior team members to do the same.
• Mentor junior engineer and lead analysis of product tradeoffs and deliver simple and intuitive products that just work.
• Develop and maintain relationships with diverse teams spanning all organizational levels to effectively articulate technology solution and gain trust and buy-in.

The Requirements:

• Bachelor's degree in Computer Science, Engineering or a related technical field; or equivalent experience.
• 8-10 years of experience on Power BI, data integration, data engineering service and data platform solutions along with leading a team including architects, engineers, quality assurance, and operations professionals.
• 7+ years of experience architecting, designing and developing large scale data solutions utilizing a mixture of AWS Cloud & Azure Cloud, RDBMS, ETL platforms.
• Solid experience in working with BI tools preferably Microsoft Power BI (Advance Modeling), Tableau, R. Qlik Sense or any other similar tool and processing engine like Apache Spark & Kafka and in integrating/querying data from multiple platforms/tools including but not limited to SQL sources, JSON, XML, CSV, REST APIs, etc
• Experience in working with AWS (redshift, ec2, glue,s3), Azure, Ms sql redshift and reddis databases.
• Strong expertise in technologies related to workflows for data engineering pipeline such as Airflow, Cloud dataflow, Kafka and Hadoop.
• Experienced in working with Python, Jinja, M and SQL languages.
• Experienced in working with warehousing technologies such as Amazon Reshift, Google big query, IBMdb2 and Teradata.
• Good understanding in Git version control, Azure DevOps, CVS, Helix, SVN and Jenkins likes (CCD) pipelines.
• Good understanding of different graph/visualization types for various business reporting needs and ability to work with a Dimensional Data Warehouse including Dims, Facts, and Star Schemas will be beneficial.
• Good understanding of various drilling concepts such as drill-down, drill-across, etc., and experience in implementing the same in graphs/reporting widgets.
• Previous experience with ETL technologies such as HEVO, Pentaho, Talend, informatica.
• Previous working experience using cloud environments and various cloud services.
• Previous experience using Docker (with EC2) and Machine Learning.
• Proven experience leading teams resulting in the successful deployment of applications built on data platforms.
• Demonstrated understanding of enterprise data warehouse, Azure cloud, big data, BI & analytics, and data management practices.

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