Data Modeller (Enterprise), at Talent Pro · Bengaluru (Bangalore) · 8 - 14 years · ₹40L - ₹47L / yr · Bootstrapped · Posted 10 Mar 2026

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.

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Hiring: Data Modeler
Experience: 6+ years
Location: Bangalore/Gurugram/Pune
Required Skills
- Hands-on experience in conceptual, logical, and physical data modeling.
- Strong knowledge of ER modeling, dimensional modeling, star/snowflake schemas, fact/dimension tables, and SCDs.
- Strong SQL skills for data profiling, validation, and quality checks.
- Experience with source-to-target mapping, data dictionaries, metadata, and data lineage.
- Proficiency in Erwin, ER/Studio, or similar modeling tools.
- Exposure to Snowflake, Databricks, Redshift, SQL Server, or other data platforms.
- Understanding of data governance, UAT, reconciliation, and Agile methodologies.
- Strong analytical, documentation, and stakeholder management skills.
Preferred Qualifications
- Experience in enterprise data warehousing or lakehouse modeling.
- Knowledge of data products, data contracts, quality SLAs, and reusable datasets.
- Exposure to dbt, data cataloging, metadata management, and governance tools.
- Ability to work independently in a fast-paced environment.
If interested please share your cv at : snigdhaattheratebeanhr.com
Data Architect – Databricks & AWS
- Strong experience in Data Architecture, Data Engineering, Databricks, Apache Spark/PySpark, Python, and Advanced SQL.
- Design and implement scalable ETL/ELT pipelines, data platforms, and Lakehouse architectures using Medallion Architecture.
- Experience with Databricks, Databricks Workflows, Unity Catalog OR Databricks Jobs
- Strong knowledge of Delta Lake, Databricks Workflows, Delta Live Tables (DLT), and dimensional data modeling.
- Hands-on experience with AWS services such as S3, Glue, IAM, Lambda, and CloudWatch.
- Experience with Apache Airflow, Data Warehouse concepts, Git/CI-CD, performance optimization, and data quality.
- Good to have exposure to Kafka/Structured Streaming, Unity Catalog, and modern data governance.
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 Architect
Experience: 7+ Years
Location: India (Ahmedabad / Hybrid/Remote)
Job Summary
We are looking for an experienced Senior Data Architect to support the modernization and enhancement of Enterprise Analytic Data Warehouse (ADW). The candidate will be responsible for evaluating existing data architecture, designing scalable data models, assessing data integration across clinical, operational and financial domains, and establishing data governance and data quality standards.
Key Responsibilities
- Assess and review the existing Enterprise Analytic Data Warehouse architecture, database structures and data integration processes.
- Design and improve enterprise data models covering clinical, operational, financial and revenue-cycle information.
- Define data architecture standards, database structures, data relationships and integration strategies.
- Evaluate data flows between source systems and the data warehouse.
- Design and review source-to-target mappings and data lineage.
- Identify architectural gaps affecting data completeness, consistency, integrity and reporting accuracy.
- Establish standardized data definitions, data governance practices and metadata management.
- Ensure consistent patient, facility, payer and other critical identifiers across different datasets.
- Support integration of billing, claims, payment, denial and accounts receivable (AR) data.
- Work with SQL and Python-based data processing solutions to investigate and validate data structures.
- Recommend improvements to warehouse scalability, performance, reliability and maintainability.
- Develop a prioritized architecture and modernization roadmap for future implementation.
- Coordinate with data engineers, analytics engineers and business stakeholders.
Required Technical Skills
- Strong experience in Data Architecture and Enterprise Data Warehousing.
- Advanced SQL and relational database concepts.
- Experience with data modelling (conceptual, logical and physical).
- Knowledge of ETL/ELT pipelines and data integration.
- Experience with data profiling, data lineage and metadata management.
- Understanding of data governance, data quality and data validation frameworks.
- Experience working with large and complex datasets.
- Python knowledge for data analysis and validation.
- Experience with cloud-based data platforms or modern data warehouse technologies.
Preferred Skills
- Experience with Databricks, Azure, AWS or similar cloud data platforms.
- Experience with healthcare data warehouses.
- Knowledge of clinical, financial, billing and claims datasets.
- Understanding of HIPAA, PHI and healthcare data security principles.
- Experience with healthcare analytics, reimbursement and revenue-cycle data.

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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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.
About Solutionara
Solutionara is an AI-led IT Consulting and Technology Services organization delivering enterprise transformation through Cloud, Integration, Data Engineering, Digital Experience, AI, and Enterprise Applications.
Headquartered in the United States with a Global Delivery Center (GDC) in Noida, India, Solutionara partners with enterprise organizations across retail, manufacturing, distribution, consumer goods, and other industries to design, implement, and support scalable technology solutions.
As a rapidly growing consulting organization, we foster a culture of ownership, innovation, collaboration, and continuous improvement, empowering our teams to contribute beyond their immediate responsibilities while delivering exceptional value to our global clients.
Every team member is expected to think like a consultant and business problem solver—understanding client objectives, challenging assumptions when appropriate, leveraging AI responsibly, and continuously identifying opportunities to improve quality, productivity, and customer outcomes.
AI is embedded into how we work, but it is an enabler—not a replacement for expertise, critical thinking, or accountability.
Role Overview
Solutionara is seeking a Senior Data Engineer with strong data engineering and database expertise to design, build, optimize, and support enterprise-scale data solutions.
This is a hands-on engineering position requiring strong SQL, Python, ETL/ELT, database, cloud, and troubleshooting capabilities. The engineer will work closely with technical leads and client stakeholders while taking ownership of major engineering components.
Location: Noida, India – Onsite | Employment Type: Full-Time | Experience: 6–9 Years
Key Responsibilities
Data Engineering
- Design, develop, test, deploy, and support scalable ETL/ELT pipelines.
- Build ingestion and transformation solutions across databases, APIs, files, and enterprise applications.
- Develop high-quality SQL and Python-based data processing solutions.
- Implement batch and incremental data-processing patterns.
- Develop reusable engineering components and frameworks.
- Support complex data migration and transformation activities.
- Perform source-to-target mapping and technical data analysis.
- Implement pipeline logging, monitoring, exception handling, and recovery mechanisms.
Database & Platform Engineering
- Design and optimize relational database schemas and data structures.
- Analyze and improve SQL/query performance.
- Support indexing, partitioning, storage optimization, and database performance.
- Implement appropriate database security and access controls.
- Support database monitoring, availability, backup/recovery, and operational requirements in collaboration with infrastructure/platform teams.
- Troubleshoot database and pipeline performance issues.
- Contribute to cloud data-platform configuration and optimization.
Data Quality
- Implement automated validation and data-quality controls.
- Develop reconciliation processes between source and target systems.
- Identify duplicate, incomplete, inconsistent, and invalid data.
- Implement cleansing, standardization, validation, and exception-management logic.
- Work with technical and business stakeholders to understand and implement business data rules.
Technical Delivery
- Convert technical designs into reliable production solutions.
- Participate in technical design and code reviews.
- Mentor junior/mid-level engineers.
- Support estimation and technical planning.
- Troubleshoot complex production and integration issues.
- Collaborate with technical leads, application teams, DevOps, QA, BI, and client teams.
- Document technical designs, mappings, configurations, operational procedures, and engineering decisions.
Consulting & AI-Led Working
- Understand the business purpose behind assigned engineering requirements.
- Raise risks, assumptions, dependencies, and potential improvements proactively.
- Communicate effectively with client and internal stakeholders.
- Use AI-assisted tools to improve coding, testing, analysis, documentation, and troubleshooting productivity.
- Independently verify AI-generated code and recommendations before implementation.
- Identify opportunities for engineering automation and process improvement.
Required Qualifications
- 6–9 years of experience in data engineering, database engineering, data integration, or related areas.
- Advanced SQL skills.
- Strong hands-on Python experience.
- Strong ETL/ELT development experience.
- Strong relational database knowledge, such as SQL Server, PostgreSQL, Oracle, or equivalent.
- Experience with data modeling and database design.
- Experience with AWS, Azure, or another major cloud platform.
- Experience with modern data technologies such as Databricks, Snowflake, Redshift, Synapse, Glue, ADF, Airflow, dbt, or equivalent.
- Experience with performance tuning and optimization.
- Experience with data validation and reconciliation.
- Strong troubleshooting and analytical skills.
- Ability to take ownership of engineering deliverables with limited supervision.
Preferred Qualifications
- Experience working with enterprise ERP, CRM, PIM, PLM, MES, or related systems.
- Experience with manufacturing, retail, distribution, or consumer-goods data.
- Experience with CI/CD and infrastructure/platform engineering practices.
- Experience with API and event-driven integrations.
- Previous consulting or technology-services experience.
What Success Looks Like
- Pipelines and databases perform reliably at enterprise scale.
- Engineering solutions are maintainable, reusable, and well documented.
- Data issues are detected and addressed systematically.
- Junior engineers receive effective technical guidance.
- Problems are owned through resolution rather than simply escalated.
- Engineering decisions reflect both technical requirements and client business objectives.
Job Overview:
We are seeking an experienced Cloud Data Engineer to the architecture, development, Data migration, ETL pipeline in cloud and optimization of a next-generation data platform. This is a development role for an individual with over 4 years of deep data engineering and data migration, data pipeline in AWS expertise, capable of driving technical direction, and delivering high-impact solutions in a fast-paced
4+ Years of hands-on, progressive experience in Cloud Data Engineering, cloud ecosystems AWS, Data Architecture
• Deep conceptual understanding of core data engineering principles, ETL/ELT patterns, and metadata management
• Ability to translate complex business needs into actionable technical requirements.
• Strong troubleshooting and problem-solving skills in distributed systems.
• Agile/Scrum teamwork capabilities and version control practices
• Insurance industry experience preferred but not mandatory
• Tools:
o Cloud Environment: AWS (S3, IAM, VPC, Glue, Lambda etc.)
o Experience with dbt Core, Iceberg, AWS Glue Catalog, AWS lambda, Redshift, Athena, Splunk, AmazonQ, AWS streaming services, Git
o Strong SQL, Pyspark and Python
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).
- Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
- Strong problem-solving, communication, and collaboration skills.
Good-to-Have Skills:
- Experience in integrating ERP data into data lakes.
- Experience with traditional ETL tools (e.g., Talend, Pentaho).
Competencies:
- 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!
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.










