Senior Data Architect

Position: Technical Architect – Data Engineering

Job Summary:

• We are looking for an experienced Technical Architect to lead the design and implementation of modern cloud-based data platforms.
• The ideal candidate should have strong expertise in Azure and/or AWS, Databricks, Snowflake, modern data architecture, and large-scale data engineering.
• The candidate will work closely with business stakeholders, architects, and engineering teams to deliver scalable, secure, and high-performance data solutions.

Key Responsibilities

• Design enterprise-scale data lakehouse and data warehouse architectures.

• Define data ingestion, transformation, and serving architecture.

• Lead architecture discussions and technical governance.

• Design scalable ETL/ELT frameworks using Databricks and Snowflake.

• Define best practices for security, performance, CI/CD, and DevOps.

• Guide engineering teams on implementation.

• Collaborate with business, product, and data governance teams.

Must Have Skills :

• Azure or AWS

• Databricks

• Snowflake

• Data Lakehouse Architecture

• PySpark

• SQL

• Data Modelling

• ETL/ELT Architecture

• Performance Optimization

• CI/CD

• Terraform or Infrastructure as Code (preferred)

Preferred

• Insurance domain

• dbt

• Unity Catalog

• Delta Lake

• Iceberg

• Azure Data Factory / AWS Glue  

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.

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

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

IMMEDIATE JOINERS ONLY

Key Responsibilities:

1                   Data Flow Mapping & Lineage

2                   Design and produce end-to-end data flow maps for critical data items – from market source/core systems, through Data Lake staging, zone 2 and consumption zone 3, to downstream reporting, dashboards and analytics use cases.

3                   Document data lineage and transformations for critical data elements identified in the Master Data Requirements exercise, ensuring traceability that is audit-defensible and supports regulatory, governance and AI-readiness needs.

4                   Map data availability by country/Data Lake against the Product Hierarchy (to profit-centre level), building the consolidated Commercial Data Landscape view of what exists, where it sits (source only, staging, or consumption) and what is not captured at all.

5                   Document cross-system dependencies and cross-border data flows, flagging data residency, privacy and regulatory considerations to the appropriate governance forums.

6                   Data Inventory, Data Model Alignment & Gap Analysis

•                    Own and mature the data asset inventory, catalogue and data dictionary aligned to the consolidated Master Data Requirements Template – resolving “Not Specified”, “TBD” and “validation required” availability statuses through structured validation with Market IT and Data Engineering.

•                    Align business data requirements to the conceptual and logical data model of the target Data Lakehouse, ensuring the dependency between data model design and lineage tracking of critical data items is explicitly documented.

•                    Perform gap and hydration analysis by market and product, quantifying the scale of data that must be brought into the Data Lakes and providing sizing input to the Data Foundation Lead, DAE architects and Data Engineering delivery plans.

•                    Contribute to the Data Consolidation Plan towards a single source of truth, including recommended sequencing based on business priority (Top 200 fields, Horizon 1–3 priorities).

•                    Stakeholder Engagement & Workshops

•                    Work hand-in-hand with the Data Foundation Lead, Data & Analytics Programme Manager, Data Engineers, DAE/infrastructure architects, Local Market IT and Business stakeholders (Regional and Market) as the connective tissue between business data needs and technical implementation.

•                    Plan and facilitate structured interviews and cross-functional validation workshops with business, technology and data stakeholders to corroborate actual operating data flows against documented processes – establishing a fact-based, evidence-backed view rather than relying on documentation alone.

•                    Translate ambiguous business asks into clear data definitions, mapping rules and acceptance criteria that Data Engineering can build against, and play back findings to senior stakeholders in clear, visual, decision-oriented formats.

•                    Manage competing priorities across multiple markets with tact, keeping momentum in an environment of constrained capacity and differing local system landscapes.

•                    Governance, Ownership & Documentation

•                    Produce and maintain the Data Ownership & Accountability Matrix – mapping data owners, stewards and custodians per data asset and highlighting ownership gaps for remediation.

•                    Classify data assets by sensitivity and business function, aligning to Data Protection Policy, PDPA and applicable regulatory expectations (e.g. MAS guidelines) in partnership with Risk & Compliance.

•                    Ensure all data flow maps, lineage records and inventory artefacts are version-controlled, audit-ready and handed over cleanly into BAU data governance processes.

•                    Produce source to Datalake mapping document and data catalogue for missing data elements to complete Datalake hydration

Key Skills

•                    Data flow mapping and lineage documentation – proven ability to draw clear, accurate source-to-consumption data flow maps across complex multi-system, multi-market landscapes.

•                    Data architecture and modelling – strong grasp of conceptual/logical data models, data lake/lakehouse zone architectures (staging, conformed, consumption), data marts and MDM concepts.

•                    Data inventory, catalogue, dictionary and metadata management; familiarity with lineage/catalogue tooling (e.g. Purview, Collibra) and diagramming tools (e.g. Visio, ErWin, Lucidchart).

•                    Hands-on data profiling and validation skills (SQL essential) to verify what actually exists in source systems and lake zones.

•                    Strong stakeholder management – this is critical: able to build trust and drive outcomes across regional leadership, market business teams, Market IT and engineering, and to facilitate effective cross-functional workshops.

•                    Insurance domain knowledge – ideally commercial and specialty lines, with an understanding of policy, claims, reinsurance and underwriting data.

•                    Data quality, governance and privacy concepts, including cross-border data considerations.

•                    Clear written and visual communication – able to make complex data landscapes understandable to executives.

Experience & Qualification Requirements:

•                    8+ years’ experience in data architecture, data business analysis or information architecture roles, with at least:

•                    3+ years documenting data flows, lineage or data landscapes across multi-system / multi-market environments.

•                    Experience in Insurance or Financial Services, ideally within data foundation, data lake or data governance programmes.

•                    Demonstrated delivery of data inventory / data mapping / current-state data landscape assessments involving both business and IT stakeholders.

•                    Relevant certification (e.g. DAMA CDMP, TOGAF, cloud data platform certifications) preferred.

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

Job Description:

We are seeking a skilled Senior Data Engineer with expertise in Databricks to join our dynamic data team. The ideal candidate will design, build, and maintain scalable data pipelines and architectures to support our organization's data-driven initiatives and leverage Databricks to process large-scale datasets, optimize data workflows, enable advanced analytics and machine learning, and integrate Power BI for data visualization and reporting.

Key Responsibilities

·        5-8 years of professional work experience in a relevant field

·        Proficient in Microsoft Fabric platform, Azure Databricks, ADF, Delta Lake, SQL Data Warehouse, Unity Catalog.

·        Good Experience on Microsoft Dynamics 365

·        Experience/ prior knowledge on semi structure data and Structured Streaming, Azure synapse, data lake, data warehouse.

·        Proficient in creating Azure Data Factory pipelines for ETL/ELT processing; copy activity, custom Azure development etc.

·        Good knowledge of SQL and Python for data manipulation, transformation, and analysis

·        Understand business requirements to set functional specifications for reporting applications

• Data Pipeline Development: Design, develop, and maintain robust, scalable data pipelines using Databricks, Apache Spark, and other cloud-based technologies.
• Data Integration: Ingest, transform, and integrate data from diverse sources, including APIs, databases, streaming platforms, and third-party systems, into Databricks for analytics and reporting.
• Power BI Integration: Develop and optimize data models and datasets in Databricks for use in Power BI, ensuring efficient data connections and high-quality visualizations.
• Performance Optimization: Optimize data workflows, API calls, and queries on Databricks and Power BI for performance, cost-efficiency, and scalability.
• Data Modeling: Build and maintain data models to support business requirements, ensuring data quality, consistency, and accessibility for analytics and reporting.
• Cloud Integration: Implement data solutions on cloud platforms (e.g., AWS, Azure, GCP) integrated with Databricks, Power BI, and API ecosystems.
• Security & Compliance: Implement data governance, security, and compliance best practices within Databricks, Power BI, and API environments.
• Technical Skills:
• Proficiency in Databricks, including Delta Lake, Spark SQL.
• Strong programming skills in Python, Scala, or Java.
• Experience with Apache Spark for big data processing.
• Knowledge of SQL for querying and transforming data.
• Proficiency in Power BI for creating data models, DAX queries, and interactive dashboards.

Preferred Qualifications

• Databricks certification (e.g., Databricks Certified Data Engineer Associate/Professional).

Experience with real-time data processing and streaming

4 - 10 years of experience in designing and buildingarchitecting highly resilient data platforms 

∙Strong knowledge of data engineering, architecture and data modeling 

∙Experience in platforms like Databricks and Snowflake 

∙Experience on building applications on cloud (AWS or Azure or Google Cloud) 

∙Strong analytical and problem-solving skills 

∙Prior experience in developing data or computation intensive (e.g. grid based) backend applications is an 

advantage 

∙OOP design skills with an understanding or at least personal interest towards the concepts of Functional 

Programming  

∙Willingness to understand and enhance other people’s code, being able to work in an environment where 

developers will oversee and work on wider components also dealing with older “legacy” code 

∙Strong programming skills (Java/ Scala / Python) skills with the willingness to pick up the other language if not 

already mastered at a sufficient level is important 

∙Spring knowledge is an advantage, but in general willingness to learn, work with and even enhance in-house 

developed frameworks is a must 

∙Prior experience in working with Git, Bitbucket, Jenkins, working with PR-s, using JIRA, following the Scrum Agile 

methodology is an advantage 

∙Prior knowledge of financial products is an advantage 

∙Bachelors or Masters in any relevant field of IT/Engineering area is an advantage  

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
• 
  

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.

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.