Cloud Data Architect

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

We are looking for an experienced Power BI Architect to lead enterprise-wide BI initiatives. This role will be responsible for designing, implementing, and governing scalable Power BI solutions across the organization. The ideal candidate will play a key role in establishing best practices, driving adoption, and owning the overall BI architecture within the Center of Excellence (CoE).

Key Responsibilities

• Lead end-to-end implementation of Power BI solutions across the enterprise
• Design scalable, secure, and high-performance BI architecture
• Act as the Power BI Architect, providing technical leadership and direction
• Own and drive BI governance, standards, and best practices within the CoE
• Collaborate with business and technology teams to translate requirements into robust BI solutions
• Define data modeling strategies, reporting frameworks, and dashboard standards
• Ensure data accuracy, consistency, and performance optimization across reports
• Support and guide development teams in Power BI implementation
• Enable enterprise-wide adoption of Power BI through training, documentation, and mentorship
• Work closely with IT/technology teams to integrate Power BI with data platforms and enterprise systems

Required Skills & Qualifications

• 10+ years of experience in BI/Data Analytics, with strong focus on Power BI
• Proven experience in enterprise-wide Power BI implementation
• Strong expertise in:
• Power BI (Desktop, Service, Gateway, Dataflows)
• Data Modeling (Star Schema, Snowflake Schema)
• DAX, Power Query (M language)
• Experience in designing and implementing BI architecture at scale
• Strong understanding of data warehousing concepts and ETL processes
• Experience working within a Center of Excellence (CoE) model
• Excellent stakeholder management and communication skills

Preferred Skills

• Experience with Azure (Azure Synapse, Data Factory, Data Lake)
• Knowledge of DevOps practices for Power BI (CI/CD pipelines)
• Exposure to governance tools and security frameworks
• Certification in Power BI / Microsoft Data Platform

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.
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Experience

8+ Years

Job Description:

Experience: 10+ Years

Job Summary

We are looking for an experienced Azure Fabric Data Architect to lead the design and implementation of an enterprise data platform on Microsoft Fabric. The role involves architecting scalable data solutions, defining data governance, and enabling AI-driven analytics for a global financial services client.

Key Responsibilities

• Design end-to-end data architecture using Microsoft Fabric.
• Build enterprise Lakehouse, Data Warehouse, and OneLake solutions.
• Define data ingestion, ETL/ELT, governance, security, and performance strategies.
• Lead architecture for AI-powered analytics, AI Agents, and enterprise chatbots using Azure AI services.
• Work with business stakeholders to translate requirements into technical solutions.
• Mentor engineering teams and provide technical leadership.

Required Skills

• Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, OneLake)
• Azure Data Engineering
• Power BI
• Azure AI Services / Azure OpenAI
• Data Architecture & Data Modeling
• SQL, Python
• Azure DevOps, CI/CD
• Strong stakeholder management and solution design experience
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Preferred: Experience in Capital Markets or Financial Services and Microsoft Azure/Fabric certifications.

NOTE: One technical round is mandatory to be taken F2F from office.

We are looking for Data engineer with strong expertise in Data warehousing to join our team.

Key skills : ab initio, ssis , Informatica, Hadoop and Teradata

Mandatory Skills (Must Have)

• SQL and Database Design (5+ years in enterprise data platforms)

• Python development for automation and platform services (5+ years)

• Linux administration and Shell Scripting in production environments

• Metadata-driven systems and data management platform experience

• Technical leadership of offshore or distributed development teams Wissen Technology

• System analysis, troubleshooting, and production support expertise

• Metadata onboarding, integration, and governance processes

• Stakeholder management and delivery ownership across multiple teams

Key Responsibilities

• Lead developers supporting the Pantheon Metadata platform and related services

• Own end-to-end delivery of metadata onboarding and enhancement initiatives

• Design scalable metadata management solutions and automation capabilities

• Collaborate with architecture, infrastructure, and application teams for enterprise integration

• Participate in solution design reviews and establish development best practices

• Prioritize enhancements with business stakeholders and manage delivery commitments

• Provide production support, troubleshooting, and platform stability improvements Wissen Technology

• Drive modernization initiatives related to metadata lifecycle management

We are looking for a Lead Data Architect to design, build, and scale our data pipelines and entity resolution systems. This role combines deep technical expertise in data engineering with hands-on experience in AI-assisted tooling, entity matching, and data integration from diverse sources. You will lead architectural decisions for our data platform, mentor engineers, and ensure our pipelines are reliable, scalable, and production-grade.

Key Responsibilities

     Architect, build, and maintain robust, scalable data pipelines that ingest, transform, and serve data from multiple internal and external sources.

     Own the end-to-end orchestration of data workflows using tools like Dagster, ensuring observability, reliability, and maintainability of pipelines.

     Design and implement entity resolution workflows — including matching, merging, and survivorship logic — using tools such as Splink, to produce clean, deduplicated, golden records.

     Build and maintain web scrapers to source data from external providers, ensuring resilience to source changes, rate limits, and data quality issues.

     Integrate and reconcile data coming from multiple, often inconsistent, sources into unified, trustworthy datasets.

     Design and maintain data models and schemas across transactional and analytical systems, ensuring consistency, scalability, and performance.

     Leverage AI/LLM-based tools and techniques to enhance data pipeline capabilities — e.g., intelligent data extraction, automated data quality checks, or AI-assisted entity matching.

     Define and enforce best practices around pipeline design, testing, monitoring, and documentation.

     Collaborate closely with data engineers, product managers, and other stakeholders to translate business requirements into scalable data architecture.

     Provide technical leadership and mentorship to the data engineering team.

Required Skills & Experience

     Strong hands-on experience building and maintaining production-grade data pipelines at scale.

     Practical experience with Dagster (or similar orchestration tools like Airflow/Prefect) for pipeline orchestration.

     Experience with Splink or similar probabilistic/deterministic record linkage tools for entity matching, merging, and survivorship.

     Strong proficiency in Python, including experience writing and maintaining web scrapers.

     Proven experience integrating and maintaining data pipelines that pull from multiple, heterogeneous data sources.

     Experience applying AI/ML tools within data engineering workflows (e.g., LLM-assisted data cleaning, extraction, or matching).

     Hands-on experience with relational and distributed databases such as PostgreSQL and Google Cloud Spanner.

     Strong understanding of data modeling principles (normalization, dimensional modeling, schema design) across OLTP and OLAP systems.

     Experience with cloud data warehousing platforms such as BigQuery, Redshift, and cloud platforms (GCP/AWS/Azure).

     Strong communication skills and experience working cross-functionally with engineering and product teams.

     Experience with distributed data processing frameworks (e.g., Spark, Dask).

     Familiarity with data governance, lineage, and cataloging tools.

     Prior experience in a lead or architect-level role guiding a data engineering team.

What We're Looking For

A technically strong, hands-on leader who can balance architectural thinking with the practical grit of debugging a flaky scraper or tuning a matching algorithm — someone who's comfortable owning both the big picture and the messy details of real-world data.

Next

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.

Sr. Data Engineer 

Location: Pune

Responsibilities 

· Lead the end-to-end design and development of scalable, high-performance data pipelines and ETL/ELT frameworks aligned with modern data engineering best practices. 

· Architect complex data integration workflows that bring together structured, semi-structured, and unstructured data from both cloud and on-premise sources. 

· Build robust real-time, batch, and on-demand pipelines with built-in observability—monitoring, alerting, and automated error handling. 

· Partner with analysts, data scientists, and business leaders to define and deliver reliable data models, quality frameworks, and SLAs that power key business insights. 

· Ensure optimal pipeline performance and throughput, with clearly defined SLAs and proactive alerting for data delivery or quality issues. 

· Collaborate with platform, DevOps, and architecture teams to build secure, reusable, and CI/CD-enabled data workflows that align with enterprise architecture standards. 

· Establish and enforce the best practices in source control, code reviews, testing automation, and continuous delivery for all data engineering components. 

· Lead root cause analysis (RCA) and preventive maintenance for critical data failures, ensuring minimal business impact and continuous service improvement. 

· Guide the team in establishing standards for data modeling, transformation logic, and governance, ensuring long-term maintainability and scalability. 

· Design and execute comprehensive testing strategies—unit, integration, and system testing—ensuring high data reliability and pipeline resilience. 

· Monitor and fine-tune data pipeline and query performance, optimizing for reliability, scalability, and cost-efficiency. 

· Create and maintain detailed technical documentation, including data architecture diagrams, process flows, and integration specifications for internal and external stakeholders. 

· Facilitate and lead discussions with business and operational teams to understand data requirements, prioritize initiatives, and drive data strategy forward. 

Qualifications 

· 7 to 10 years of hands-on experience in data engineering roles with a proven record of building scalable and secure data platforms. 

· Over 5 years of experience in scripting languages such as Python for data processing, automation, and ETL development. 

· 4+ years of experience with Snowflake, including performance tuning, security model design, and advanced SQL development. 

· 5+ years of experience with data integration tools such as Azure Data Factory, Fivetran, or Matillion. 

· 5+ years of experience in writing complex, highly optimized SQL queries on large datasets. 

· Proven experience integrating and managing APIs, JSON, XML, and webhooks for data acquisition. 

· Hands-on experience with cloud platforms (Azure/AWS) and orchestration tools like Apache Airflow or equivalent. 

· Experience with CI/CD pipelines, automated testing, and code versioning tools (e.g., Git). 

· Familiarity with dbt or similar transformation tools and best practices for modular transformation development. 

· Exposure to data visualization tools like Power BI for supporting downstream analytics is a plus. 

· Strong interpersonal and communication skills with the ability to lead discussions with technical and business stakeholders. 

Education 

Bachelor’s or Master’s degree in Computer Science/Information technology or related field. 

Equivalent academic and work experience can be considered.