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EXL

Analyzes business data and runs outsourced operations

Data Modeler

Data ManagementConfirmed live in the last 24 hours
Full-timeGurugram, Haryana, IndiaNo salary listedIn-person

About the Job

Requirements

  • 7–10 years of industry implementation experience with one or more data modeling tools such as Erwin, ERStudio, or PowerDesigner.
  • A minimum of 8 years of data architecture, data modeling (Data Vault, dimensional, or 3NF), or similar experience.
  • 5–7 years of management experience.
  • Experience working with dimensionally modeled data.
  • A bachelor's degree or equivalent experience; a master's degree is preferred.
  • Understanding of cloud and on-premises architectures, including Azure, AWS, GCP, or Snowflake.
  • Experience in data analysis and profiling.
  • Strong data warehousing and OLTP systems knowledge from an integration perspective.
  • Strong understanding of data integration best practices and concepts.
  • Strong SQL skills; scripting experience is preferred.
  • Strong knowledge of all phases of the system development life cycle.
  • Experience with major database and big data platforms such as RDS, Aurora, Redshift, Databricks, MySQL, PostgreSQL, Oracle, Hadoop, or Snowflake.
  • Understanding and experience with data architecture philosophies such as dimensional modeling, ODS, and Data Vault.
  • Understanding of modern data warehouse capabilities and technologies such as real-time, cloud, and big data.
  • Consulting experience is preferred.

Responsibilities

  • Translate business needs into data models that support long-term solutions.
  • Work with the Application Development team to implement data strategies, build data flows, and develop conceptual data models.
  • Create and maintain conceptual, logical, and physical data models and corresponding metadata using best practices to ensure high data quality and reduce redundancy.
  • Optimize and update logical and physical data models to support new and existing projects.
  • Develop best practices for standard naming conventions and coding practices to ensure data model consistency.
  • Recommend opportunities to reuse data models in new environments.
  • Reverse-engineer physical data models from databases and SQL scripts.
  • Evaluate data models and physical databases for variances and discrepancies.
  • Validate business data objects for accuracy and completeness.
  • Analyze data-related system integration challenges and propose appropriate solutions.
  • Develop data models according to company standards; guide system analysts, engineers, programmers, and others on project limitations and capabilities, performance requirements, and interfaces.
  • Review modifications to existing software to improve efficiency and performance.
  • Examine new application designs and recommend corrections when required.
  • Assist with and support data architecture direction, including data movement approaches and architecture and technology strategy; ensure data architecture deliverables are developed, standards and guidelines are followed, architecture is implemented, and technical developers receive project- or business-unit-level support.
  • Coordinate and consult with project managers, client business staff, client technical staff, and project developers on data architecture best practices and other data-related matters at project or business-unit levels.

Desired Qualifications

  • Document user requirements and business processes and translate business processes into technical documents.
  • Create data architect designs and documents for business processing requirements.
  • Analyze and audit requirements and business processes.
  • Prepare business matrix diagrams identifying business processes, dimensions, facts, conformed dimensions, junk dimensions, and degenerate dimensions.
  • Participate in review and collaboration sessions on business processes and canonical (BOM) modeling.
  • Profile source system data to identify business processes and requirements using operational system data.
  • Design and capture business processes and map them to conceptual data models.
  • Model business processes with UML diagrams using Rational Rose.
  • Prepare test scenarios based on understanding of business process flows.
  • Assist with process model development by identifying business process needs and requirements and modeling them into usable, business-driven data processes.
  • Participate in requirements-gathering, design-review, and code-review meetings; analyze business processes and optimize existing extract stored procedures.
  • Redefine attributes and relationships in reverse-engineered models and cleanse unwanted tables and columns as part of data analysis.
  • Review entities and relationships in engineered models and cleanse unwanted tables and columns as part of data analysis.
  • Conduct logical data analysis and data modeling joint application design (JAD) sessions and document data-related standards.
  • Perform data analysis to support mapping and transformation of data from legacy systems to physical data models.
  • Gather accurate data through data analysis and functional analysis.
  • Conduct logical data modeling and data analysis.
  • Develop SQL queries to extract data from test and production databases for data analysis and data quality checks.
  • Use TOAD, SQL Assistant, Tortoise SVN, and Redgate SQL Compare for data analysis and related work.
  • Develop Oracle PL/SQL procedures, packages, and functions for day-to-day data analysis.
  • Analyze application views, functions, and triggers; tune performance and fix missing or incorrectly mapped data.
  • Perform data mapping, data analysis, and gap analysis between legacy systems and vendor packages.
  • Perform data profiling and data analysis using SQL queries to identify data issues and anomalies.
  • Define data architecture and data management strategies, data standards, and data architecture.
  • Consolidate and generate database standards and naming conventions to enhance enterprise data architecture processes.
  • Develop activity-centered data architecture and process architecture for automated data extraction.
  • Analyze, document, and articulate customers' current data warehouse and data mart architecture.
  • Generate logical data models for legacy databases through reverse engineering and document them to support forward engineering.
  • Design and implement procedures for mapping interface data between legacy systems and a new implementation.
  • Revise and rewrite design specifications and establish internal procedures for product certification.
  • Design standards and procedures for metadata management in structured and unstructured data environments.
  • Mentor existing staff on data administration processes, procedures, and standards.
  • Create standards and procedures for metadata collection and repository maintenance.
  • Design and develop complex database procedures and packages.
  • Develop business-specific custom reports using PL/SQL procedures.
  • Establish auditing procedures to ensure data integrity.
  • Develop stored procedures to implement business logic.
  • Design functional testing standard operating procedures.
  • Provide teams with required stored procedures, packages, and access to data.
  • Develop and optimize database structures, stored procedures, dynamic management views, DDL triggers, cursors, and user-defined functions.

About the Company

EXL

Analyzes business data and runs outsourced operations

EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1999

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