Job Description

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Responsibilities

• Fluent in the Microsoft tool suite including SharePoint, Excel, Word, PowerPoint, Visio.
• Evaluates technological choices (Server/hardware related) by querying providers and understanding enough about implications to make choices for the organization that have and appropriate balance between cost /benefit today and future implications and limitations
• Experience in at least 2 - AWS based data warehouse design and implementation including.
• Evaluates complex situations using multiple sources of information filters, validates and interprets dynamic material
• Manages and appropriately escalates delivery impediments, risks, issues, and changes associated to the product development initiatives
• Responsible for Designing, development and delivering of high-performance Energy Analytics platform.
• Analyze and resolve complex problems associated with the development of Energy Analytics platform.
• Gather and address technical and design requirements.
• Manage day to day work of development team along with roadmap and implementation with ownership of implementation timeline.
• Perform user testing, A/B testing, and other continuous improvement projects
• Develop communication, admin and management tools for Fusion platform using AWS and related technologies.
• Stay abreast with new innovations and the latest technology trends and explore ways of leveraging these for improving the product in alignment with the business.

• Experience:

• B Tech/B.E. in computer science or any other allied fields from top schools.
• 9+ years overall experience with 2+ years of experience working as data warehouse Technical Manager in high performing scalable environment on AWS.
• Preferable:

• Experience and understanding of Energy/Utility domains.
• Must have skills:

• You will bring this to the table Ability to work in ambiguous situations with unstructured problems and anticipate potential issues risks Demonstrated experience in building data pipelines in data analytics implementations such as Data Lake and Data Warehouse At least 2 instances of end-to-end implementation of the data processing pipeline.
• Experience configuring or developing custom code components for data ingestion, data processing, and data provisioning, using Big data & distributed computing platforms such as as AWS Firehose, Kafka, Glue, Athena, S3, Apache Spark on Cloud platforms such as AWS or Google.
• Hands-on experience developing enterprise solutions using designing and building frameworks, enterprise patterns, database design, and development in 2 or more of the following areas, End-to-end implementation of Cloud data engineering solution Kafka Spark streaming, transform and storage in HDFS.
• Realtime solution using Spark streaming, Kafka, Kinesis Distributed compute solution (Spark Storm, Hive).
• Distributed storage and NoSQL storage (Cassandra, S3, NoSQL)
• Batch solution and distributed computing using ETL (Spark SQL Spark Data frame AWS Glue)
• Manage Performance tuning, memory optimization and partitioning.
• Development of Frameworks, reusable components, accelerators, CI/CD automation
• Expert level in Python using Kafka.
• Proficiency in data modelling, for both structured and unstructured data, for various layers of storage
• Ability to collaborate closely with business analysts, architects, and client stakeholders to create technical specifications.
• Ensure quality of code components delivered by employing unit testing and test automation techniques including CI in DevOps environments.
• Ability to profile data, assess data quality in the context of business rules, and incorporate validation and certification mechanisms to ensure data quality.
• Ability to review technical deliverables, mentor and drive technical teams to deliver quality technical deliverables.
• Understand system Architecture and provide component-level design specifications, both high level, and low-level design.