Job Description
Responsibilities
Interprets and delivers impactful strategic plans improving data integration, data quality, and data delivery in support of business initiatives and roadmaps
Designs the structure and layout of data systems, including databases, warehouses, and lakes
Selects and designs database management systems that meet the organizations needs by defining data schemas, optimizing data storage, and establishing data access controls and security measures
Defines and implements the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platforms
Designs processes for the ETL process from various sources into the organizations data systems
Translates high-level business requirements into data models and appropriate metadata, test data, and data quality standards
Manages senior business stakeholders to secure strong engagement and ensures that the delivery of the project aligns with longer-term strategic roadmaps
Simplifies the existing data architecture, delivering reusable services and cost-saving opportunities in line with the policies and standards of the company
Leads and participates in the peer review and quality assurance of project architectural artifacts across the EA group through governance forums
Defines and manages standards, guidelines, and processes to ensure data quality
Works with IT teams, business analysts, and data analytics teams to understand data consumers needs and develop solutions
Evaluates and recommends emerging technologies for data management, storage, and analytics
Design, create, and implement logical and physical data models for both IT and business solutions to capture the structure, relationships, and constraints of relevant datasets
Build and operationalize complex data solutions, correct problems, apply transformations, and recommend data cleansing/quality solutions
Effectively collaborate and communicate with various stakeholders to understand data and business requirements and translate them into data models
Create entity-relationship diagrams (ERDs), data flow diagrams, and other visualization tools to represent data models
Collaborate with database administrators and software engineers to implement and maintain data models in databases, data warehouses, and data lakes
Develop data modeling best practices, and use these standards to identify and resolve data modeling issues and conflicts
Conduct performance tuning and optimization of data models for efficient data access and retrieval
Incorporate core data management competencies, including data governance, data security and data quality
Job Requirements
Education:
A bachelors degree in computer science, data science, engineering, or related field
Experience:
At least five years of relevant experience in design and implementation of data models for enterprise data warehouse initiatives
Experience leading projects involving data warehousing, data modeling, and data analysis
Design experience in Azure Databricks, PySpark, and Power BI/Tableau
Skills:
Ability in programming languages such as Java, Python, and C/C++
Ability in data science languages/tools such as SQL, R, SAS, or Excel
Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks)
Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata
Understanding of entity-relationship modeling, metadata systems, and data quality tools and techniques
Ability to think strategically and relate architectural decisions and recommendations to business needs and client culture
Ability to assess traditional and modern data architecture components based on business needs
Experience with business intelligence tools and technologies such as ETL, Power BI, and Tableau
Ability to regularly learn and adopt new technology, especially in the ML/AI realm
Strong analytical and problem-solving skills
Ability to synthesize and clearly communicate large volumes of complex information to senior management of various technical understandings
Ability to collaborate and excel in complex, cross-functional teams involving data scientists, business analysts, and stakeholders
Ability to guide solution design and architecture to meet business needs
Expert knowledge of data modeling concepts, methodologies, and best practices
Proficiency in data modeling tools such as Erwin or ER/Studio
Knowledge of relational databases and database design principles
Familiarity with dimensional modeling and data warehousing concepts
Strong SQL skills for data querying, manipulation, and optimization, and knowledge of other data science languages, including JavaScript, Python, and R
Ability to collaborate with cross-functional teams and stakeholders to gather requirements and align on data models
Excellent analytical and problem-solving skills to identify and resolve data modeling issues
Strong communication and documentation skills to effectively convey complex data modeling concepts to technical and business stakeholders
Interprets and delivers impactful strategic plans improving data integration, data quality, and data delivery in support of business initiatives and roadmaps
Designs the structure and layout of data systems, including databases, warehouses, and lakes
Selects and designs database management systems that meet the organizations needs by defining data schemas, optimizing data storage, and establishing data access controls and security measures
Defines and implements the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platforms
Designs processes for the ETL process from various sources into the organizations data systems
Translates high-level business requirements into data models and appropriate metadata, test data, and data quality standards
Manages senior business stakeholders to secure strong engagement and ensures that the delivery of the project aligns with longer-term strategic roadmaps
Simplifies the existing data architecture, delivering reusable services and cost-saving opportunities in line with the policies and standards of the company
Leads and participates in the peer review and quality assurance of project architectural artifacts across the EA group through governance forums
Defines and manages standards, guidelines, and processes to ensure data quality
Works with IT teams, business analysts, and data analytics teams to understand data consumers needs and develop solutions
Evaluates and recommends emerging technologies for data management, storage, and analytics
Design, create, and implement logical and physical data models for both IT and business solutions to capture the structure, relationships, and constraints of relevant datasets
Build and operationalize complex data solutions, correct problems, apply transformations, and recommend data cleansing/quality solutions
Effectively collaborate and communicate with various stakeholders to understand data and business requirements and translate them into data models
Create entity-relationship diagrams (ERDs), data flow diagrams, and other visualization tools to represent data models
Collaborate with database administrators and software engineers to implement and maintain data models in databases, data warehouses, and data lakes
Develop data modeling best practices, and use these standards to identify and resolve data modeling issues and conflicts
Conduct performance tuning and optimization of data models for efficient data access and retrieval
Incorporate core data management competencies, including data governance, data security and data quality
Job Requirements
Education:
A bachelors degree in computer science, data science, engineering, or related field
Experience:
At least five years of relevant experience in design and implementation of data models for enterprise data warehouse initiatives
Experience leading projects involving data warehousing, data modeling, and data analysis
Design experience in Azure Databricks, PySpark, and Power BI/Tableau
Skills:
Ability in programming languages such as Java, Python, and C/C++
Ability in data science languages/tools such as SQL, R, SAS, or Excel
Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks)
Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata
Understanding of entity-relationship modeling, metadata systems, and data quality tools and techniques
Ability to think strategically and relate architectural decisions and recommendations to business needs and client culture
Ability to assess traditional and modern data architecture components based on business needs
Experience with business intelligence tools and technologies such as ETL, Power BI, and Tableau
Ability to regularly learn and adopt new technology, especially in the ML/AI realm
Strong analytical and problem-solving skills
Ability to synthesize and clearly communicate large volumes of complex information to senior management of various technical understandings
Ability to collaborate and excel in complex, cross-functional teams involving data scientists, business analysts, and stakeholders
Ability to guide solution design and architecture to meet business needs
Expert knowledge of data modeling concepts, methodologies, and best practices
Proficiency in data modeling tools such as Erwin or ER/Studio
Knowledge of relational databases and database design principles
Familiarity with dimensional modeling and data warehousing concepts
Strong SQL skills for data querying, manipulation, and optimization, and knowledge of other data science languages, including JavaScript, Python, and R
Ability to collaborate with cross-functional teams and stakeholders to gather requirements and align on data models
Excellent analytical and problem-solving skills to identify and resolve data modeling issues
Strong communication and documentation skills to effectively convey complex data modeling concepts to technical and business stakeholders
💡 Quick Summary
Seeking a career-building opportunity? The Sr Data Architect position is now open for candidates interested in the Data Entry Jobs sector. This role in India offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Data Entry Jobs is a plus.
