Data Modeller (Enterprise) at TalentXO · Bengaluru (Bangalore), Mumbai, Hyderabad, Gurugram · 8 - 14 years · ₹30L - ₹40L / yr · Profitable · Posted 17 Mar 2026

Role & Responsibilities
drives large-scale data modernization and AI readiness for global enterprises. We are looking for an experienced Data Modeler to design, standardize, and maintain enterprise data models across our modernization initiatives — ensuring consistency, quality, and business alignment across cloud data platforms.
The person will be responsible for translating business requirements and data flows into robust conceptual, logical, and physical data models across multiple domains (Customer, Product, Finance, Supply Chain, etc.). You will work closely with Data Architects, Engineers, and Governance teams to ensure data is structured, traceable, and optimized for analytics and interoperability across platforms like Snowflake, Dremio, and Databricks.
Key Responsibilities-
- Develop conceptual, logical, and physical data models aligned with enterprise architecture standards.
- Engage with Business Stakeholders: Collaborate with business teams, business analysts and SMEs to understand business processes, data lifecycles, and key metrics that drive value and outcomes.
- Value Chain Understanding: Analyze end-to-end customer and product value chains to identify critical data entities, relationships, and dependencies that should be represented in the data model.
- Conceptual and Logical Modeling: Translate business concepts and data requirements into conceptual and logical data models that capture enterprise semantics and support analytical and operational needs.
- Physical Data Modeling: Design and implement physical data models optimized for performance and scalability
- Semantic Layer Design: Create semantic models that enable business access to data via BI tools and data discovery platforms.
- Data Standards and Governance: Ensure models comply with enterprise data standards, naming conventions, lineage tracking, and governance practices.
- Implement naming conventions, data standards, and metadata definitions across all models.
- Collaboration with Data Engineering: Work closely with data engineers to align data pipelines with the logical and physical models, ensuring consistency and accuracy from ingestion to consumption.
- Manage version control, lineage tracking, and change documentation for models.
- Participate in data quality and governance initiatives to ensure trusted and consistent data definitions across domains.
- Create and maintain a business glossary in collaboration with the governance team.
Ideal Candidate
- Strong Enterprise Data Modeller profile (Modern Data Platforms)
- Mandatory (Experience 1) – Must have 7+ years of experience in Data Modeling or Enterprise Data Architecture, with strong hands-on expertise in designing conceptual, logical, and physical data models for enterprise data platforms
- Mandatory (Experience 2) – Must have Strong hands-on experience with enterprise data modeling tools such as Erwin, ER/Studio, PowerDesigner, SQLDBM, or similar enterprise data modeling tools
- Mandatory (Experience 3) – Must have Deep understanding of dimensional modeling (Kimball / Inmon methodologies), normalization techniques, and schema design for modern data warehouse environments.
- Mandatory (Experience 4) – Proven experience designing data models for modern data platforms such as Snowflake, Databricks, Redshift, Dremio, or similar cloud data warehouse / lakehouse systems.
- Mandatory (Experience 5) – Must have strong SQL expertise and schema design skills, with the ability to validate data model implementations and collaborate closely with data engineering teams
- Mandatory (Education) – Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related technical field.
- Preferred (Experience 1) – Should have familiarity with data governance, metadata management, lineage, and business glossary tools such as Collibra, Alation, or Microsoft Purview.
- Preferred (Experience 2) – Exposure to data integration pipelines and ETL frameworks such as Informatica, DBT, Airflow, or similar tools.
- Preferred (Data Management) – Understanding of master data management (MDM) and reference data management principles.
- Preferred (Domain) – Experience working with high-tech or manufacturing data domains, including customer, product, or supply chain data models

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About the Role
You'll be at the forefront of designing and implementing robust data platform solutions that power advanced analytics, AI, and machine learning. Working with modern cloud technologies, you'll build scalable data foundations that enable clients to make smarter, data-driven decisions.
Key Responsibilities
- Build scalable data pipelines using Snowflake, AWS, GCP, and Databricks.
- Design and optimize data models for AI and machine learning workloads.
- Develop reliable data foundations for MLOps, governance, and data lineage.
- Integrate data from multiple sources into modern data platforms.
- Leverage Snowpark ML and Snowflake's native AI capabilities.
- Ensure data platforms are secure, scalable, and high-performing.
What We're Looking For
- 5+ years of hands-on experience with Snowflake.
- Strong proficiency in SQL and Python.
- Experience with AWS, Azure, or GCP.
- Knowledge of cloud storage services such as S3, ADLS, or GCS.
- Strong understanding of Dimensional Modeling and Data Vault.
- Experience with Scala or Java is a plus.
Tech Stack
- Data Warehouse: Snowflake
- Programming: SQL, Python, Scala (Good to Have), Java (Good to Have)
- Cloud: AWS, Azure, GCP
- Storage: S3, ADLS, GCS
- AI/ML: Snowpark ML, MLOps
Perks & Benefits
- Public Speaking & Communication Program
- Mentoring Program with Senior Support Leads
- 360° Progress Reviews
- Weekly Learning Sessions & Guilds
- Paid Certifications
- Hackathons & Innovation Days
- Recognition & Rewards Programs
- Team Socials & Annual Offsites
- Employee Assistance Program (24/7 Wellbeing Support)
The Data People Shaping Tomorrow
Our client helps organizations unlock the power of data through modern cloud, analytics, and AI solutions. We believe in creating an environment where talented technologists can learn, innovate, and make a real impact while building cutting-edge data platforms for global clients. If you're passionate about data engineering and want to work with the latest technologies in AI, cloud, and analytics, we'd love to hear from you.
Job Title: Senior Data Engineer
Position Summary
We are seeking a highly skilled Data Engineer with strong expertise in reporting infrastructure, data modeling, and analytics platforms. This role will focus on building scalable reporting solutions, optimizing data pipelines, and enabling data-driven decision-making across the organization. The ideal candidate will have deep experience with databases, data warehousing, and complex query development. While Ruby on Rails experience is beneficial, the primary emphasis is on data engineering and reporting systems.
Key Responsibilities
- Design, develop, and maintain reporting infrastructure and data platforms.
- Build and optimize complex SQL queries, data models, and reporting datasets.
- Develop scalable ETL/ELT pipelines and data integration processes.
- Design and maintain database schemas to support analytics and reporting requirements.
- Collaborate with business stakeholders to understand reporting needs and translate them into technical solutions.
- Implement data quality, governance, and performance best practices.
- Support and enhance enterprise reporting solutions and dashboards.
- Work with large-scale datasets in cloud data warehouse environments.
- Troubleshoot reporting issues and optimize database performance.
- Partner with engineering and product teams to establish sustainable data architecture.
Must Have: Technical Skills
- PostgreSQL
- Snowflake
- Advanced SQL
- Data Modeling
- Data Warehousing
- Reporting & Analytics Infrastructure
- ETL/ELT Development
- Query Performance Tuning
Success Profile:
The ideal candidate is a data-focused engineer who enjoys working with complex datasets, designing scalable reporting solutions, and building foundational infrastructure that empowers analytics and business intelligence teams. They should be comfortable navigating databases, optimizing queries, and translating business reporting needs into robust technical implementations.
Experience Range: 5-10 years
Role Type: Individual Contributor / Senior Engineer
Primary Focus: Reporting Infrastructure, Data Engineering, Data Warehousing, and Analytics Enablement.
We are looking for a Data Engineer with at least 1 year of hands-on experience building solutions on Snowflake. The candidate should be comfortable designing, building, and managing reliable data pipelines that move data from multiple sources into a central data platform.
Responsibilities
- Build and maintain data pipelines for ingesting, transforming, and loading data into Snowflake
- Design scalable data models, schemas, tables, and views in Snowflake
- Develop ETL/ELT workflows using SQL, Python, or data orchestration tools
- Integrate data from APIs, databases, files, and third-party platforms
- Monitor pipeline performance, failures, data quality, and freshness
- Optimize Snowflake queries, warehouses, storage, and compute usage
- Implement incremental loads, change data capture, and scheduled workflows
- Work with engineering and business teams to understand data requirements
- Maintain documentation for pipelines, datasets, and data transformations
Requirements
- 1+ year of hands-on experience working with Snowflake
- Strong SQL skills and experience writing complex queries
- Experience building and managing ETL or ELT data pipelines
- Knowledge of data warehousing concepts, dimensional modelling, and data quality
- Experience with Python or another scripting language
- Familiarity with orchestration tools such as Airflow, Dagster, Prefect, dbt, or similar
- Understanding of APIs, relational databases, file formats, and cloud storage
- Ability to troubleshoot pipeline failures and performance issues
- Strong analytical, problem-solving, and communication skills
Good to Have
- Experience with dbt and Snowflake Tasks, Streams, Snowpipe, or Dynamic Tables
- Knowledge of AWS, Azure, or Google Cloud
- Experience with Kafka or other streaming platforms
- Familiarity with CI/CD, Git, monitoring, and data governance practices
- Experience integrating ERP, finance, or operational systems
Role Summary:
We are looking for an experienced Snowflake Lead to lead the design, development, migration, and optimization of enterprise data platforms using Snowflake. The candidate will provide technical leadership to data engineering teams and work closely with architects, business stakeholders, and application teams.
Key Responsibilities
- Lead the architecture and development of scalable Snowflake data warehouse solutions.
- Design and develop scalable Azure Data Factory (ADF) pipelines for API-based and batch data ingestion, implementing parameterized workflows, scheduling, and error handling.
- Build and optimize enterprise Snowflake data warehouse solutions using Snowflake SQL, Streams, Tasks, Stored Procedures, VARIANT data type, and LATERAL FLATTEN for semi-structured JSON processing.
- Integrate GraphQL and REST APIs using OAuth 2.0, implementing secure API authentication, JSON parsing, and API validation using Postman.
- Develop cloud-based data ingestion solutions using Azure Data Lake Storage Gen2 (ADLS) as the landing layer and Azure Key Vault for secure credential management.
- Design metadata-driven ELT frameworks with incremental loading, audit logging, watermark processing, and automated data orchestration.
- Optimize Snowflake performance through warehouse sizing, query tuning, clustering strategies, Time Travel, Cloning, and warehouse management best practices.
- Collaborate with DevOps teams using Azure DevOps for source control, CI/CD deployment, release management, and Agile delivery.
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- Work closely with business stakeholders, solution architects, and cross-functional teams to deliver secure, scalable, and high-performance cloud data platform solutions.
Thanks,
Mounika P
About Us:
The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
Job Summary:
We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.
As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.
Key Responsibilities:
- Design, develop, test, and maintain optimal data pipeline and ETL architectures.
- Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
- Prepare and optimize data for predictive and prescriptive modeling.
- Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
- Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
- Utilize big data tools and frameworks to optimize data acquisition and preparation.
- Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
- Develop and curate data models for analytics, dashboards, and reports.
- Conduct code reviews, maintain production-level code, and implement testing approaches.
- Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
- Drive innovation and implement efficient new approaches to data engineering tasks.
Must-Have Skills:
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
- 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
- 3–5 years of experience designing and implementing data warehouse solutions.
- Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
- Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
- Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
- Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
- Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
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Good-to-Have Skills:
- Experience in integrating ERP data into data lakes.
- Experience with traditional ETL tools (e.g., Talend, Pentaho).
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- Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
- Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
- Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
- Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
Why Join Us?
- Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
- Work on impactful projects that make a difference across industries.
- Opportunities for professional growth and continuous learning.
- Competitive salary and benefits package.
Application Details
Ready to make an impact? Apply today and become part of the QX Impact team!
Location: Hyderabad / Chennai
Experience: 5+ years
Employment type: Full-time, permanent
Work Hours: General Shift
website: www.amazech.com
Qualifications:
- B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Data Science, or related disciplines.
- Strong academic background with relevant industry experience in Data Engineering and Data Warehousing.
Key Responsibilities:
· Design, develop, and maintain scalable data warehouse solutions using Snowflake.
· Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.
· Develop and support ETL processes using Talend to ensure reliable and efficient data movement.
· Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.
· Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.
· Debug and troubleshoot Python-based data processing scripts and automation workflows.
· Implement best practices for data quality, testing, deployment, and code reviews.
· Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.
· Monitor, optimize, and maintain data warehouse performance and operational stability.
· Create and maintain technical documentation, data models, and process workflows.
Required Skills and Experience:
· Strong hands-on expertise in Snowflake Data Warehouse.
· Advanced SQL skills with experience handling large-scale datasets.
· Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.
· Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.
· Experience developing and maintaining ETL solutions using Talend.
· Proficiency in Python for scripting, debugging, automation, and data processing.
· Experience integrating UI, API, and Data Warehouse workflows.
· Strong problem-solving and analytical skills.
· Experience with testing, code reviews, and deployment best practices.
· Excellent communication and stakeholder management skills.
Responsibilities and JD
Job Description: We are looking for a Senior Developer with strong expertise in PySpark, Databricks, and Snowflake to build scalable data engineering solutions and enterprise data platforms.
Key Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
- Develop batch and real-time data processing solutions for structured and semi-structured data.
- Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
- Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
- Develop scalable data models, data marts, and data warehouse solutions.
- Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
- Implement data quality, validation, governance, and security controls.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
- Manage source control and CI/CD deployments using Git and Azure DevOps.
- Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
- Mentor junior team members and participate in code reviews and technical design discussions.
Required Skills: PySpark, Databricks, Snowflake, Python, SQL.
Experience: 5+ years of Data Engineering experience with strong hands-on expertise in PySpark, Databricks, and Snowflake.
Location – Hyderabad (Hybrid)
Work Experience – 5 to 7 years
CTC – upto 20 LPA
Roles & Responsibilities:
· We are looking for a Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines.
· Integration of data from multiple sources or vendors to provide the holistic insights from data.
· You are expected to build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms etc.
· Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues.
· Should have experience in client interaction.
· Experience in mentoring juniors and providing required guidance.
Required Technical Skills
· Extensive hands on experience in Python, Pyspark, SQL, Dataiku.
· Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.
· Working knowledge in Databricks, Redshift, ADF etc.
· Hands-on experience in cloud services like Azure, AWS- S3, Glue, Lambda, CloudWatch, Athena.
· Sound knowledge in end-to-end Data management, Data ops, quality and data governance.
· Familiar with SFDC, Waterfall/ Agile methodology.
· Strong domain knowledge in Pharma domain/ life sciences commercial data operations.
Qualifications
· Bachelor’s or master’s Engineering/ MCA or equivalent degree.
· 5-7 years of relevant industry experience as Data Engineer.
· Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.
· High motivation, good work ethic, maturity, self-organized and personal initiative.
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· Excellent written and verbal communication skills.
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Dear Candidate,
Greeting from NAM Info Pvt Ltd.
We have a role for Data Engineer position with NAM Info.
This role will be permanent with NAM info and deploy to client
location NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA.
Work Mode: WORK FROM OFFICE
A decent hike can be provided based on current CTC
Interview Mode: Virtual
Role Descriptions:
Exp Range: 7 - 10 years
City Locations: NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA
Key Responsibilities*
Role: Data Engineer
Location: ~NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA
Skills: Digital: Databricks, Azure Data Factory
Experience Required: 8-10
Descriptions:
Good information and sound knowledge in Azure Synapse Analytics Azure Data Factory (ADF)Big Data technologies and data processing frameworks Azure Data Warehouse and associated Azure data platform services Data integration| data modelling| and performance optimization
Desire candidate
- Candidate should have valid PF.
Regards,
NAM Info
Solution Architect – AZURE Data Engineering
Job Overview
We are looking for an experienced Solution Architect – Data Engineering with strong expertise in designing data solutions and hands-on experience with Azure, Synapse, PySpark, Data Warehousing, and Data Lakes. The ideal candidate should have strong architectural and data engineering knowledge.
Key Responsibilities
- Design and implement scalable data architecture and solutions.
- Develop and manage Data Warehouse and Data Lake architectures.
- Design data platforms using Medallion Architecture.
- Lead Data Engineering and ETL activities.
- Work with Azure Synapse Analytics for data processing and analytics.
- Develop data solutions using PySpark / Apache Spark.
- Define and implement data validation and data quality processes.
- Collaborate with business, data, and technology teams to deliver effective data solutions.
Required Skills
- Strong experience in Solution Architecture / Data Architecture.
- Strong knowledge of Data Warehouse and Data Lake architecture.
- Good understanding of Medallion Architecture.
- Strong experience in Data Engineering and ETL.
- Hands-on experience with Microsoft Azure and Azure Synapse Analytics.
- Strong knowledge of PySpark / Apache Spark.
- Experience with Data Validation and Data Quality.
- Good communication and stakeholder management skills.
Experience
8+ Years





