Sr. Data Architect

This role is for one of Weekday’s clientsSalary range: Rs 1000000 - Rs 4300000 (ie INR 10 - 43 LPA)Min Experience: 8+ yearsLocation: Hyderabad, Telangana, IndiaJobType: full-timeAs a Data Architect, you will design and build the data architecture for one or more customer domains within a multi-squad data engineering practice serving Critical Infrastructure, Magenta Service Center, and Credit Risk & Fraud. You will report into the US-based team and work directly with the Tech Lead, Senior Data Engineers, Technical Product Managers, and Senior BI Analysts — turning customer outcomes into well-designed data products on Databricks Lakehouse, Snowflake CDW, and Microsoft Fabric.This is a hands-on architect role focused on design and delivery. You will produce the pipeline designs, data models, integration patterns, and migration plans your squad builds against — and you'll be in the code on the harder pieces of the work, not just on the whiteboard. You will partner with the Tech Lead on platform-level standards and decisions, but the day-to-day focus is owning the architecture for your squad's data products and helping the engineers on your squad ship them well.We pride ourselves on encouraging a culture of innovation, agile ways of working, and transparency in all we do. Join us in embodying the spirit of the Un-carrier and make a tangible impact.RequirementsWhat You'll Do:Design end-to-end data architecture for your squad's data products — including Databricks Lakehouse medallion design (Bronze / Silver / Gold), Snowflake CDW models, Unity Catalog structure, and the integration patterns that connect source systems to consumption layers.Produce the technical designs for major pipeline builds: ingestion patterns, transformation logic, schema design, partitioning and performance choices, data quality controls, and operational considerations.Contribute code on the harder pieces — complex transformations, performance-critical pipelines, integration scaffolding, reference implementations the rest of the squad builds from.Lead design reviews for your squad's deliverables; identify design risks before they reach production and propose alternatives that are both pragmatic and durable.Partner with the Tech Lead and other architects on platform-level patterns — ingestion frameworks (including the Unified Ingestion Framework), streaming standards, semantic-layer design, data product certification criteria — and apply those patterns consistently in your squad's work.Design and lead complex legacy migrations: SQL Server Lakehouse, Alteryx Databricks, on-prem Oracle / SAP Lakehouse, Snowflake Lakehouse interop — from extraction through validation, rebuild, and decommission.Partner with the Real-Time Integration Engineering team on event-driven design for streaming use cases (Kafka, Azure Event Hub, Delta Live Tables) when your squad needs them.Partner with the enterprise Semantic Layer team on per-domain semantic model design in Microsoft Fabric — measures, dimensions, deduplication with adjacent domains, and certification readiness.Translate architecture decisions into terms that land with Technical Product Managers, customer-side stakeholders, and non-engineers — so design choices are understood, not just shipped.Apply enterprise data standards by default: data classification (including USGCI), encryption of sensitive elements, access controls, audit logging, SOX-controlled data flows where applicable, and AI-ready data foundations.Internalize the customer context behind your squad's work and make design decisions consistent with it; choose the fastest responsible path to meet the immediate need, then decide what should become a durable, reusable pattern.Drive clarity in ambiguity — surface design risks early, name the decisions to be made, identify owners, and propose a path forward across cross-team dependencies.Mentor Senior and mid-level data engineers on the squad — through design reviews, pair-design sessions, and direct code feedback.What You'll Bring:7–10 years of data engineering or data platform engineering experience, with at least 2 years in a data architect, data modeler, or senior engineer capacity owning end-to-end designs.Strong hands-on Databricks experience: Delta Lake, Unity Catalog, Databricks Workflows, Structured Streaming, and performance tuning.Working experience with Microsoft Fabric — OneLake, Fabric Data Engineering, and exposure to Fabric IQ semantic layer design.Snowflake CDW experience — warehouse design, performance tuning, and a working understanding of Snowflake / Databricks (Iceberg) interop patterns.Experience with real-time streaming architectures (Kafka, Azure Event Hub, Delta Live Tables, or comparable) — at least at the design and integration level.Strong proficiency in PySpark and Spark SQL for distributed data transformation and pipeline design.Experience designing ERP or enterprise-system ingestion pipelines, with familiarity with Change Data Capture (CDC) patterns.Experience designing or leading legacy platform migrations — extraction, validation, rebuild, and decommission.Fluency in cross-functional conversations — able to walk a Technical Product Manager, customer stakeholder, or non-engineer through a design decision and have it land.Customer-minded engineering builds with the downstream consumer and business outcome in mind; uses sound judgment on speed vs. durability.Drives clarity in ambiguity — surfaces design risks early, names decisions, identifies owners, and proposes a path forward.Pragmatic, direct communication — clear and concise in design docs, reviews, and stand-ups; able to explain technical decisions to non-engineers.Agile delivery experience (Jira, Confluence, CI/CD).Must Have Skills:Azure Data Factory, Azure Databricks, Microsoft Fabric, Delta Lake, SQL, Spark, PySpark, Python, Snowflake , DBT(Data Build Tools)Real time Streaming Pipelines (Kafka/Azure Event Hub/Deepio)Data Modelling, ETL/ELT Pipelines, Scheduling Tools(like Control-M, Autosys etc.),Unity Catalog, RBACCI/CD, GITLAB, System Designing, Cloud Data Architectures, Data Governance, Optimizations and Performance TuningNice-to-Have:Azure certifications (DP-203, AZ-900, DP-900),Agile / ScrumAI Tools(Claude, Co-pilot etc.) & AI/ML-ready data preparationFamiliarity with USGCI, SOXAlteryx/PowerBIBackground in Finance, Procurement, Network Infrastructure, or Credit Risk data domains

This role is for one of Weekday’s clients
Salary range: Rs 1000000 - Rs 4300000 (ie INR 10 - 43 LPA)

Min Experience: 8+ years
Location: Hyderabad, Telangana, India
JobType: full-time

As a Data Architect, you will design and build the data architecture for one or more customer domains within a multi-squad data engineering practice serving Critical Infrastructure, Magenta Service Center, and Credit Risk & Fraud. You will report into the US-based team and work directly with the Tech Lead, Senior Data Engineers, Technical Product Managers, and Senior BI Analysts — turning customer outcomes into well-designed data products on Databricks Lakehouse, Snowflake CDW, and Microsoft Fabric.

This is a hands-on architect role focused on design and delivery. You will produce the pipeline designs, data models, integration patterns, and migration plans your squad builds against — and you'll be in the code on the harder pieces of the work, not just on the whiteboard. You will partner with the Tech Lead on platform-level standards and decisions, but the day-to-day focus is owning the architecture for your squad's data products and helping the engineers on your squad ship them well.

We pride ourselves on encouraging a culture of innovation, agile ways of working, and transparency in all we do. Join us in embodying the spirit of the Un-carrier and make a tangible impact.

Requirements

What You'll Do:

Design end-to-end data architecture for your squad's data products — including Databricks Lakehouse medallion design (Bronze / Silver / Gold), Snowflake CDW models, Unity Catalog structure, and the integration patterns that connect source systems to consumption layers.

Produce the technical designs for major pipeline builds: ingestion patterns, transformation logic, schema design, partitioning and performance choices, data quality controls, and operational considerations.

Contribute code on the harder pieces — complex transformations, performance-critical pipelines, integration scaffolding, reference implementations the rest of the squad builds from.

Lead design reviews for your squad's deliverables; identify design risks before they reach production and propose alternatives that are both pragmatic and durable.

Partner with the Tech Lead and other architects on platform-level patterns — ingestion frameworks (including the Unified Ingestion Framework), streaming standards, semantic-layer design, data product certification criteria — and apply those patterns consistently in your squad's work.

Design and lead complex legacy migrations: SQL Server Lakehouse, Alteryx Databricks, on-prem Oracle / SAP Lakehouse, Snowflake Lakehouse interop — from extraction through validation, rebuild, and decommission.

Partner with the Real-Time Integration Engineering team on event-driven design for streaming use cases (Kafka, Azure Event Hub, Delta Live Tables) when your squad needs them.

Partner with the enterprise Semantic Layer team on per-domain semantic model design in Microsoft Fabric — measures, dimensions, deduplication with adjacent domains, and certification readiness.

Translate architecture decisions into terms that land with Technical Product Managers, customer-side stakeholders, and non-engineers — so design choices are understood, not just shipped.

Apply enterprise data standards by default: data classification (including USGCI), encryption of sensitive elements, access controls, audit logging, SOX-controlled data flows where applicable, and AI-ready data foundations.

Internalize the customer context behind your squad's work and make design decisions consistent with it; choose the fastest responsible path to meet the immediate need, then decide what should become a durable, reusable pattern.

Drive clarity in ambiguity — surface design risks early, name the decisions to be made, identify owners, and propose a path forward across cross-team dependencies.

Mentor Senior and mid-level data engineers on the squad — through design reviews, pair-design sessions, and direct code feedback.

What You'll Bring:

7–10 years of data engineering or data platform engineering experience, with at least 2 years in a data architect, data modeler, or senior engineer capacity owning end-to-end designs.

Strong hands-on Databricks experience: Delta Lake, Unity Catalog, Databricks Workflows, Structured Streaming, and performance tuning.

Working experience with Microsoft Fabric — OneLake, Fabric Data Engineering, and exposure to Fabric IQ semantic layer design.

Snowflake CDW experience — warehouse design, performance tuning, and a working understanding of Snowflake / Databricks (Iceberg) interop patterns.

Experience with real-time streaming architectures (Kafka, Azure Event Hub, Delta Live Tables, or comparable) — at least at the design and integration level.

Strong proficiency in PySpark and Spark SQL for distributed data transformation and pipeline design.

Experience designing ERP or enterprise-system ingestion pipelines, with familiarity with Change Data Capture (CDC) patterns.

Experience designing or leading legacy platform migrations — extraction, validation, rebuild, and decommission.

Fluency in cross-functional conversations — able to walk a Technical Product Manager, customer stakeholder, or non-engineer through a design decision and have it land.

Customer-minded engineering builds with the downstream consumer and business outcome in mind; uses sound judgment on speed vs. durability.

Drives clarity in ambiguity — surfaces design risks early, names decisions, identifies owners, and proposes a path forward.

Pragmatic, direct communication — clear and concise in design docs, reviews, and stand-ups; able to explain technical decisions to non-engineers.

Agile delivery experience (Jira, Confluence, CI/CD).

Must Have Skills:

Azure Data Factory, Azure Databricks, Microsoft Fabric, Delta Lake, SQL, Spark, PySpark, Python, Snowflake , DBT(Data Build Tools)

Real time Streaming Pipelines (Kafka/Azure Event Hub/Deepio)

Data Modelling, ETL/ELT Pipelines, Scheduling Tools(like Control-M, Autosys etc.),

Unity Catalog, RBAC

CI/CD, GITLAB, System Designing, Cloud Data Architectures, Data Governance, Optimizations and Performance Tuning

Nice-to-Have:

Azure certifications (DP-203, AZ-900, DP-900),

Agile / Scrum

AI Tools(Claude, Co-pilot etc.) & AI/ML-ready data preparation

Familiarity with USGCI, SOX

Alteryx/PowerBI

Background in Finance, Procurement, Network Infrastructure, or Credit Risk data domains

At Weekday (backed by YC; also Product Hunt #1 product of the day), we are building the next frontier in hiring. We have built the largest database of white collar talent in India and have built outreach tools on top of it to generate highest response rates.

At Weekday (backed by YC; also Product Hunt #1 product of the day), we are building the next frontier in hiring. We have built the largest database of white collar talent in India and have built outreach tools on top of it to generate highest response rates.