AI & Data
In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment.
The AI & Data team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. The offering portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets.
AI & Data will work with our clients to:
- Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms
- Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions
- Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements
Data Engineer
The position is suited for individuals who have the ability to work in a constantly challenging environment and deliver effectively and efficiently. As a Data Engineer, you will be an integral member of our Data & Analytics team responsible for design and development of pipelines using cutting edge technologies.
Key Responsibilities –
• Data Modeling: Create and maintain conceptual, logical, and physical data models that accurately represent the organization's data assets. These models may include entity-relationship diagrams (ERDs), data flow diagrams, and schema designs.
• Requirements Gathering: Collaborate with business analysts, data analysts, and other stakeholders to understand their data needs and requirements. Translate these requirements into data model specifications.
• Data Standardization: Define and enforce data standards, naming conventions, and data definitions to ensure consistency and clarity across the organization.
• Database Design: Work closely with database administrators (DBAs) to design and optimize database schemas based on the data models. Ensure that databases are efficient, scalable, and well-structured.
• Data Integration: Facilitate the integration of data from various sources into the organization's data environment. Ensure that data is transformed and mapped appropriately to meet business needs.
• Data Governance: Participate in data governance initiatives by establishing data quality rules, data lineage, and data ownership guidelines. Monitor and enforce data governance policies.
• Documentation: Maintain comprehensive documentation of data models, data dictionaries, and metadata. Ensure that all changes to data models are properly documented and communicated.
• Performance Optimization: Collaborate with developers and DBAs to optimize database performance. Identify and resolve performance bottlenecks related to data access and storage.
• Data Security: Implement data security measures to protect sensitive and confidential data. Define access controls and data encryption strategies as needed.
• Data Analysis Support: Support data analysts and data scientists by providing well-structured data models that facilitate data analysis and reporting.
• Data Migration: Assist in data migration projects by ensuring that data models are consistent between source and target systems. Verify data integrity during migration.
• Professionals should possess a clear understanding of current data models
• Should be able to clearly articulate end-to-end data pipelines with analysis and accomplishment.
• Implementing data pipelines and ETL processes within AWS
• Must possess the ability to construct data pipelines utilizing Glue and allocate cloud resources.
• Should be capable of conducting data analysis, executing data quality checks, and rectifying data quality problems in collaboration with business stakeholders or Product Owners
• Required to adhere to leading practices to design pipelines in line with industry standards
• Will be collaborating with key stakeholders to address critical issues as they arise.
Qualifications
• 3-6 years of proficient experience with AWS ETLs, Glue, EMR, S3 & Athena
• Expert in languages e.g., Python, Pyspark
• Advanced knowledge of database management systems SQL
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills to work with cross-functional teams.
• Experience with version control practices and CICD Process (Git, Bamboo, etc.)
• Understanding of Financial Services Industry- IMRE (preferred)
Primary Skills:
• AWS Glue
• Athena
• SQL
• Python
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