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Senior Data Engineer- Data Modeler

Senior Data Engineer- Data Modeler

QuantiphiBengaluru, Karnataka, India
17 days ago
Job description

Company Profile :

Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.

Some company highlights :

  • Quantiphi has seen 2.5x growth YoY since its inception in 2013
  • Winner of the "Machine Learning Partner of the year" award from Google for two consecutive years - 2017 and 2018
  • Winner of the "Social Impact Partner of the year" award from Google for 2019
  • Headquartered in Boston, with 700+ data science professionals across different offices

Role & Responsibilities :

  • Data Modeler with strong Conceptual, Logical and Physical Data Modeling skills, having
  • experience in requirements gathering, creating data mapping documents, writing functional

    specifications, queries for Data Warehouse, Data Lake, Lakehouse, DataMart, OLTP, OLAP

    applications.

  • Extensive experience in Entity-Relational, Data Vault and Dimensional Data modeling for creating
  • ER Diagrams using Erwin, ER / Studio, Enterprise Architect and PowerDesigner data modeling

    tools.

  • Integral part of the Data Management team performing Data Extraction, Data Analysis, Data
  • Cleansing, Data Mapping and Data Profiling exercises using Informatica Analyst and other

    profiling tools.

  • Worked on industry standard models such as ACORD for insurance,
  • Involved in the Database Design for Operational Data Store working with DBAs and ETL
  • Architects using Data Vault Modeling approach.

  • Design, develop, and implement highly scalable data capture and transformation processes
  • Suggest best modeling approach to the client based on their requirement and target architecture
  • Analyze and understand the Datasets and guide the team in creating Source to Target Mapping
  • and Data Dictionaries,capturing all relevant details

  • Profile the Data sets to generate relevant insights
  • Define Data Modelling Best Practices and ensure implementation of Best Practices across
  • projects

  • Optimize the Data Models and work with the Data Engineers to define the Ingestion logic,
  • ingestion frequency and data consumption patterns

  • Work with QE team to define the right testing strategy
  • Drives automation in modeling activities
  • Collaborate with Business Stakeholders, Data Owners, Business Analysts, Architects to design
  • and develop next generation data platform

  • Closely monitor the Project progress and provide regular updates to the leadership teams on the
  • milestones,impediments etc

  • Create effective ETLs / ELTs to move large volumes of data from various operational systems to
  • dimensional data models for analytics consumption

  • Act as principal designer and reviewer for new data models, make data architectural decisions
  • Work with the database engineering and DBAs to create optimal physical data models (transactions,
  • normalized and dimensional models etc.)

  • Manage data modeling repository, and data modeling process and support model-driven
  • development

  • Define and govern data modeling / design standards, tools, best practices, and related development
  • methodologies

  • Champion Data Lineage, Metadata Management, and Data Quality Analysis processes
  • Collaborate with Business Data Analysts to design and model Business Intelligence Semantic layers for
  • optimized information access

  • Expand and grow data existing platform capabilities to solve new data problems and challenges
  • Ensure all automated processes preserve data integrity by managing the alignment of data availability
  • and integration processes

  • Identify opportunities for new data acquisition and new uses for existing data resources
  • Research and make recommendations for new data management technologies and software
  • engineering practices. Collaborate on decisions around the use of new tools and practices

  • Define data retention policy, establish data governance best practices, and create automated anomaly
  • detection services

  • Document and update business continuity and disaster recovery procedures
  • Engage in ongoing collaboration with data architects, modelers, and other members to achieve
  • common goals

  • Provide guidance to development teams regarding best practices and design patterns for analytics
  • solutions. Coach and provide guidance to junior team members

  • Produce and maintain support documentation for ongoing operations.
  • Act as support to troubleshoot and resolve technical issues with production data models and services
  • Excellent communication, influencing, and facilitation skills, in particular for
  • problem-solving / troubleshooting activities

  • Experience in client-facing roles
  • Assertiveness in dealing with people at all levels within and outside of the delivery organization,
  • including partner and client organizations

    Required Skills :

  • 10+ years of experience with hybrid data environments that leverage both distributed and relational database technologies to support analytics services (Oracle, IMB DB2, GCP)
  • Solid understanding of data warehousing principles, architecture, and its implementation in complex environments.
  • Good experience in OLTP and OLAP systems
  • Excellent Data Analysis skills
  • Good understanding of one or more ETL tools and data ingestion frameworks.
  • Experience as a designer of complex Dimensional data models for analytics services
  • Experience with various testing methodologies and user acceptance testing.
  • Experience on one or more cloud platforms (e.g. AWS, Azure, GCP)
  • Understanding of Data Quality and Data Governance
  • Understanding of Industry Data Models
  • Experience in leading the large teams
  • Experience with processing large datasets from multiple sources.
  • Ability to operate effectively and independently in a dynamic, fluid environment.
  • Good understanding of agile methodology
  • Strong verbal and written communications skills with experience in relating complex concepts to
  • non-technical users.

  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely
  • Proven ability to lead and drive projects and assignments to completion
  • Exposure to Data Modeling Tools
  • ○ ERwin

    ○ Power Designer

    ○ Business Glossary

    ○ ER / Studio

    ○ Enterprise Architect,

    ○ MagicDraw

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