Greetings Everyone
Who are we?
For the past 20 years, we have powered many Digital Experiences for the Fortune 500. Since 1999, we have grown from a few people to more than 4000 team members across the globe that are engaged in various Digital Modernization. For a brief 1 minute video about us, you can check https://youtu.be/uJWBWQZEA6o.
What will you do? What are we looking for?
Data Modeler / Data Analyst
- Job Description :
- 5 + years of experience in Data Modeling & Data Analyst and should have excellent communication and leadership skills. Financial Domain knowledge is plus.
- Should have in depth understanding or executed new concepts like Data Lakehouse and should have worked on Big Data data sources / tools such as Hive , S3 , Trino , HUE , etc
- Should have done Data Modeling for Fortune 100 organizations and databases atleast 10 TB in size
- Should have done complex (100+ entities/tables) Data Modeling programs in both on-prem and cloud environments .
- Experience in designing normalized, denormalized, relational, dimensional, star and snowflake schemas for cloud, big data and on prem databases using any one of these data modeling tools (Erwin R1, ER/Studio, Toad Data Modeler, etc)
- Extensive Data Modeling experience in same or similar bigdata and cloud databases such as Hive, Redshift, Snowflake and on prem databases such as Oracle, SQL Server and DB2
- Should have led Data Model workshops with business and technology stakeholders
- Should have written complex SQL queries for data analysis, generated, deployed and altered DDL
- Should have implemented Bill Inmon and Ralph Kimball methodologies to design data warehouses
- Should have worked atleast 4 projects using Agile/SAFe methodology
- Should have in depth understanding on Data Warehousing, Data Analysis, Data Profiling, Master Data Management (MDM), Data Quality, Data Lineage, Data Dictionary, Data Mapping, Data Policy and Data Governance
- Should have cross global location experience and been part of a team of atleast 20+ members in a global delivery model
- Should have experience in gathering business requirements by collaborating with business users, stakeholders and SMEs
- Should have experience in working with product managers, project managers, business users, applications development team members, DBA teams and Data Governance team on a daily basis to analyze requirements, design, development and deployment technical solutions
- Responsibilities:
- Participate in JAD, workshops and/or business requirements sessions to understand, capture and detail data modeling requirements
- Analyze client landscape and architectures to find the best data sources needed for the business requirements
- Determine appropriate data architecture suitable for the business requirements
- Perform detailed data analysis on source data, profile data, identify data cardinality, granularity and data quality issues
- Define enterprise abbreviation and data modeling naming standards
- Design data quality and cleansing rules based on profiling results to increase quality of data
- Create data flow architecture across multiple zones (raw, refined, curated, BI zones)
- Design conceptual, logical and physical data models across all data zones based on business needs
- Create Data Dictionary & DDLs for the created Data Model
- Create normalized and/or denormalized structures to manage usability and performance
- Design source to target mapping documents with transformation rules to ingest data from source tables to target environment across all the data zones
- Create security document to assign database access to users accordingly
- Design partitioning and CDC strategy across various subject areas and data zones based on business needs
- Work with business, ETL and BI teams to identify and design data models for KPIs
- Design test cases for data modeling requirements
- Create and deliver Data Model (Conceptual, logical & physical), DDL, Data Architecture document, Data Dictionary and Design document with Security Rules, CDC Strategy, Data Quality/Cleansing Rules & S2T Mapping document with transformation rules
- Support stakeholders, ETL & BI teams during data pipeline development
- Participate in onshore/nearshore/offshore calls as required to support the data pipeline development
- Need to have overlap with Onsite team till 10-11 am Pacific time , for attending scrum ceremonies or to have onsite interaction .
Location : Offshore
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