Senior Data Architect

Full-time

Company Description

Endava

Job Description

Roles and Responsibilities.

Proficiency in data modeling and design, including SQL development and database administration

Develop and document business process models to illustrate current and future states

Analyze data to identify trends, patterns, and insights that inform business decisions

Propose and design technical and process solutions that meet business needs and objectives

Deliver insights on potential areas of growth, optimization, and improvements

Problem-Solving. The ability to identify problems, analyze potential solutions, and implement the most effective solution is critical in data analysis projects

Support business intelligence strategies with quantitative analysis

Ability to implement common data management and reporting technologies, as well as the basics of columnar and NoSQL databases, data visualization, unstructured data, and predictive analytics

The ability to create interactive dashboards and detailed reports presenting data insights in a clear and accessible manner to stakeholders

Strong communication skills (oral and written)

Qualifications

Candidates with 10 to 12+ years of experience with Azure SQL, Responsible for Architecting, designing, hands on Database management.

Solution Design & Architecture

Design scalable Azure SQL architectures

Recommend optimal architecture based on:

Application Workload

Concurrency

Data volume

Hands-On experience in Azure Database Migration Service (DMS) for large databases

Ability to manage large volumes of Data

Data Model & Schema Design

Redesign schema for:

Performance

Scalability

Apply:

Normalization vs denormalization trade-offs

Partitioning strategies

Data archiving strategies

Define:

Data lifecycle management

Workload & Capacity Planning

Design solutions for:

o High concurrency systems

o Burst workloads

Recommend:

o vCore vs DTU models

o Serverless vs provisioned

o Elastic pool strategies

Cost Optimization Architecture

Analyze current spend and design:

o Right-sized compute tiers

o Auto-scaling strategies

Recommend:

o Serverless for intermittent workloads

o Optimize Infrastructure resources for Elastic pools based on Data I/O

Data Integration & Ecosystem Design

o Azure Data Factory

o Synapse Analytics

o Event-driven pipelines (Event Hub, Service Bus)

Ensure:

o Efficient data movement

Minimal latency

Mandatory SQL Server / Azure SQL DBA Expertise

Candidate must have strong hands-on experience in:

Microsoft SQL Server and Azure SQL Database administration

Database sizing, file growth, storage management, tempdb, transaction log management

Backup and restore strategies: full, differential, transaction log, copy-only, point-in-time recovery

Recovery models: simple, full, bulk-logged

High availability and disaster recovery concepts

Database maintenance: index rebuild/reorganize, statistics update, integrity checks

Handling production incidents related to space, logs, blocking, deadlocks, slow queries, failed jobs, and ETL failures

Query Performance Tuning & Execution Plan Analysis

Candidate must be able to:

Analyze actual and estimated execution plans

Identify table scans, index scans, key lookups, missing indexes, implicit conversions, parameter sniffing, bad joins, spills, incorrect cardinality estimates, and outdated statistics

Tune stored procedures, views, joins, aggregations, and ETL queries

Diagnose blocking, deadlocks, wait types, CPU pressure, memory pressure, and I/O bottlenecks

Use Query Store, DMVs, Extended Events, SQL Profiler where applicable, Azure Query Performance Insight, and Azure Monitor

Explain cases where query tuning does not improve performance and identify non-query bottlenecks such as storage, network, concurrency, locking, application design, or resource tier limitations

Data Integration, ETL Architecture & Data Quality

Candidate should have hands-on experience in:

Designing robust ETL/ELT pipelines using Azure Data Factory, Synapse Pipelines, SSIS, or equivalent tools

Handling schema evolution when source systems add, remove, or change columns

Designing schema enforcement and schema drift handling strategies

Implementing staging, landing, quarantine/error tables, reject records, audit tables, and reconciliation checks

Designing retry, restartability, idempotency, and failure recovery mechanisms

Handling bad source records without failing the complete load where business rules allow

Implementing data validation, data profiling, duplicate handling, null checks, referential integrity checks, and data quality rules

Working with multiple source systems and designing scalable ingestion frameworks

Data Warehouse & Dimensional Modeling

Candidate must be able to:

Explain and design OLTP vs OLAP architecture

Design star schema and snowflake schema models

Define fact tables, dimension tables, measures, surrogate keys, slowly changing dimensions, and conformed dimensions

Define grain of fact tables and explain how grain impacts measures, aggregation, and reporting accuracy

Design data marts and reporting layers for Power BI or similar BI tools

Separate operational workloads from analytical workloads using appropriate architecture patterns

Database Technology Selection

Candidate should be able to:

Compare SQL and NoSQL databases

Recommend appropriate database technology based on data model, consistency, scalability, transaction requirements, query patterns, and reporting needs

Understand use cases for relational databases, document databases, key-value stores, columnar stores, and analytical stores

Explain trade-offs between ACID consistency, schema flexibility, performance, and scalability

DevOps & Automation

CI/CD pipelines for DB deployments

Perform database provisioning, configuration, and upgrades

Monitoring & Troubleshooting

Using tools like

Azure Monitor

Log Analytics

Query Performance Insight

Troubleshoot database issues

Connectivity

Performance bottlenecks

Failures

Mandatory Sub Skill: Power BI or any other reporting tool

Qualifications

B.E, B.Tec

Additional Information

At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives - because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.

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