
Quantiphi - Senior Data Engineer/Modeler - OLTP/OLAP Apps
3 weeks ago
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 & Responsibilities :
- 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 Skills :
- 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. 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
(ref:hirist.tech)
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