SQL Server 2016, MSBI, Power BI

Position Responsibilities :

The Database Architect is responsible for the design, optimization, and evolution of the database layer supporting enterprise applications in cloud environments. This role focuses on ensuring efficient data access patterns, scalable query workloads, and robust database architecture capable of supporting high-volume and high-concurrency systems.

This role goes beyond traditional database administration and requires deep technical expertise in SQL query optimization, database internals, and performance diagnostics. The Database Architect analyzes how applications interact with the database and guides improvements in schema design, data access patterns, and system scalability.

As a senior technical leader, the Database Architect helps define long-term strategies for scalable and efficient data architecture while working closely with engineering teams to promote best practices for database design and SQL development.

KEY RESPONSIBILITIES

Database Architecture & Optimization

• Design and evolve database architectures for scalable enterprise systems.
• Define efficient data access patterns that support high concurrency and large datasets.
• Improve schema design, indexing strategies, and query patterns.
• Ensure database designs support both transactional and data consumption workloads.

SQL Performance Engineering

• Analyze and optimize complex SQL queries and execution plans.
• Improve database performance through indexing strategies, statistics management, and query tuning.
• Investigate workload behaviour and recommend architectural improvements.

Data Access & Systems Thinking

• Provide guidance on scalable approaches for retrieving and delivering data for data-intensive application features.
• Recommend architectural strategies such as data aggregation, caching, or pre-computed datasets where appropriate.
• Apply systems thinking to improve how data is modeled, accessed, and delivered across the application.

Advanced Diagnostics

• Diagnose database behaviour using tools such as Query Store, Extended Events, and execution plan analysis.
• Analyze query performance, wait statistics, and workload patterns to identify optimization opportunities.

Collaboration & Technical Leadership

• Partner with engineering teams to guide scalable SQL development and data access practices.
• Participate in architecture and design discussions involving database interactions.
• Document best practices and architectural recommendations.

AI-Assisted Engineering

• Use AI-assisted tools to accelerate query analysis, diagnostics, and workload investigations.
• Validate AI-generated insights through empirical testing and database telemetry.

Qualifications :

TECHNICAL SKILLS & EXPERTISE

Database & SQL Server (Required)

• Advanced SQL Server performance tuning, including query optimization, execution plan analysis, and index design
• Strong experience diagnosing and resolving deadlocks using Extended Events and deadlock graphs
• Deep understanding of locking, blocking, and transaction behaviour, including wait statistics and lock escalation
• Experience optimizing stored procedures, including mitigation of parameter sniffing and plan cache management
• Strong knowledge of indexing strategies, including covering indexes and filtered indexes
• Solid understanding of statistics, cardinality estimation, and query optimizer behaviour

Performance Analysis Tools (Required)

• Experience using SQL Server Profiler and Extended Events for workload diagnostics
• Advanced execution plan analysis using SSMS or Azure Data Studio
• Familiarity with SET STATISTICS IO/TIME for query performance evaluation
• Strong experience using Query Store to analyse query performance and plan behaviour
• Ability to diagnose issues through wait statistics and blocking chain analysis

Enterprise Application Data Architecture

• Strong understanding of database design within multi-tier enterprise applications
• Experience optimizing database workloads supporting high-concurrency systems and large datasets
• Understanding how application query patterns influence database performance
• Familiarity working with application platforms such as .NET, APIs, or modern web frameworks

Cloud & Enterprise Database Environments

• Experience working with cloud-hosted database environments
• Understanding of scalability considerations in enterprise systems
• Experience analyzing and optimizing database workloads in production environments

QUALIFICATIONS

• 8+ years of experience working with enterprise database systems
• Proven expertise in SQL performance tuning and database workload optimization
• Strong experience in analysing execution plans and database performance behaviour
• Experience collaborating with engineering teams on data architecture and query design
• Strong analytical and problem-solving skills

AI-FIRST MINDSET REQUIREMENT

We value engineers who view AI as a productivity multiplier. The ideal candidate actively leverages AI tools to accelerate diagnostics, analyze database workloads, and uncover optimization opportunities while applying strong engineering judgment to validate results

Location: Mumbai, Maharashtra, India

Sector: Technology, Information & Media

Company Size: 500 - 1,000 Employees

Employment: Full-Time, Permanent

Experience: 10 - 14 Years (Engineering Leadership)

Level: Engineering Manager / Group EM

ABOUT THIS MANDATE :

Recruiting Bond has been exclusively retained by one of India's most prominent and well-established digital platform organisations operating at the intersection of Technology, Information, and Media to identify and place an exceptional Engineering Manager who can lead engineering teams through an enterprise-wide AI adoption and digital transformation agenda.

This is a high-impact, hands-on leadership role at the nexus of people, product, and technology. The organisation is executing one of the most ambitious AI transformation programmes in its sector and this Engineering Manager will be a core driver of that change. You will lead multiple squads, own engineering delivery end-to-end, embed AI tooling and practices into the team's DNA, and shape the engineering culture of tomorrow.

We are seeking leaders who code when it matters, who build systems and teams with equal conviction, and who view AI not as a trend but as a fundamental shift in how great software is built.

THE OPPORTUNITY AT A GLANCE :

AI-First Engineering Culture :

• Own AI adoption across your squads - from LLM tooling integration to automation-first delivery workflows. Make AI a default, not an afterthought.

Hands-On Engineering Leadership :

• Stay close to the code. Lead architecture reviews, unblock engineers, and set the technical bar - not just the management agenda.

People & Org Builder :

• Grow engineers into leaders. Build squads of 615 across functions. Drive hiring, career frameworks, and a culture of psychological safety.

KEY RESPONSIBILITIES :

1. Hands-On Technical Engagement :

• Remain deeply embedded in the technical work participate in design reviews, architecture decisions, and critical code reviews
• Set and uphold the engineering quality bar : performance benchmarks, security standards, test coverage, and release quality
• Provide technical direction on backend platform strategy, API design, service decomposition, and data architecture
• Identify and resolve systemic technical debt and architectural risks across team-owned services
• Unblock engineers by diving into complex problems debugging, pair programming, and system analysis when it matters
• Own key technical decisions in collaboration with Tech Leads and Principal Engineers; balance pragmatism with long-term sustainability

2. AI Adoption, Integration & Transformation (2026 Mandate) :

• Define and execute the team's AI adoption roadmap - from developer tooling to product-facing AI features
• Champion the integration of GenAI tools (GitHub Copilot, Cursor, Claude, ChatGPT) across the full engineering workflow coding, testing, documentation, incident response
• Embed LLM-powered capabilities into the product : recommendation engines, intelligent search, conversational interfaces, content generation, and predictive systems
• Lead evaluation and adoption of AI-assisted SDLC practices : automated code review, AI-generated test suites, intelligent observability, and anomaly detection
• Partner with Data Science and ML Platform teams to productionise ML models with robust MLOps pipelines
• Build team literacy in prompt engineering, RAG (Retrieval-Augmented Generation), and AI agent frameworks
• Create an experimentation culture : run structured AI pilots, measure productivity impact, and scale what works
• Stay ahead of the AI tooling landscape and advise senior leadership on strategic AI investments and engineering implications

3. People Leadership & Team Development :

• Lead, manage, and grow squads of 6 - 15 engineers across seniority levels (L2 through L6 / Junior through Staff)
• Conduct structured 1 : 1s, career growth conversations, and development planning with every direct report
• Design and execute personalised AI upskilling programmes ensure every engineer develops practical AI fluency by end of 2026
• Build and maintain a high-performance team culture : clarity of ownership, accountability, fast feedback loops, and psychological safety
• Drive performance management fairly and rigorously recognise top performers, manage underperformance constructively
• Lead technical hiring end-to-end : define job requirements, conduct bar-raising interviews, and make data-driven hire decisions
• Contribute to engineering career frameworks and level definitions in partnership with the VP / Director of Engineering

4. Engineering Delivery & Execution Excellence :

• Own end-to-end delivery for multiple product squads from planning and scoping through production release and post-launch stability
• Implement and refine agile delivery frameworks (Scrum, Kanban, Shape Up) calibrated to squad needs and product cadence
• Drive predictable delivery : maintain healthy sprint velocity, manage WIP limits, and ensure dependency resolution across teams.
• Establish and own engineering KPIs : DORA metrics (deployment frequency, lead time, MTTR, change failure rate), uptime SLOs, and velocity trends
• Lead incident management : build blameless post-mortem culture, own RCA processes, and drive systemic reliability improvements
• Balance technical debt repayment with feature velocity negotiate prioritisation transparently with Product leadership

5. Strategic Leadership & Cross-Functional Influence :

• Serve as the primary engineering partner for Product, Design, Data, and Business stakeholders translate ambiguity into executable engineering plans
• Participate in quarterly roadmap planning, capacity forecasting, and OKR definition for engineering teams
• Represent engineering in leadership forums articulate technical constraints, risks, and opportunities in business terms
• Contribute to org-wide engineering strategy : platform investments, build-vs-buy decisions, and shared infrastructure priorities
• Build relationships across geographies (Mumbai HQ + distributed teams) to maintain alignment and delivery cohesion
• Act as a culture carrier and ambassador for engineering excellence, innovation, and responsible AI use

AI TRANSFORMATION LEADERSHIP 2026 EXPECTATIONS :

In 2026, Engineering Managers at this organisation are expected to be active architects of AI transformation not passive observers. The following outlines the specific AI leadership expectations for this role :

AI Developer Productivity

• Drive measurable uplift in developer velocity through AI tooling adoption. Target : 30%+ reduction in code review cycle time and 40%+ increase in test coverage automation by Q3 2026.

LLM & GenAI Product Features

• Own delivery of GenAI-powered product capabilities : intelligent content, semantic search, personalisation, and conversational UX in production, at scale.

AI-Augmented Observability

• Implement AI-driven monitoring and anomaly detection pipelines. Reduce MTTR by leveraging predictive alerting, intelligent runbooks, and auto-remediation scripts.

Team AI Fluency :

• Build mandatory AI literacy across all engineering levels.
• Every engineer understands prompt engineering basics, AI ethics guardrails, and responsible AI deployment practices.

Responsible AI Governance :

• Partner with Security, Legal, and Data Privacy to ensure all AI deployments meet compliance standards, bias mitigation requirements, and explainability benchmarks.

TECHNOLOGY STACK & DOMAIN FAMILIARITY REQUIRED :

• Languages: Java/ Go/ Python/ Node.js /PHP /Rust (must be hands-on in at least 2)
• Cloud: AWS / GCP / Azure (multi-cloud exposure strongly preferred)
• AI & GenAI: OpenAI / Anthropic / Gemini APIs /LangChain /LlamaIndex / RAG / Vector DBs / GitHub
• Copilot: Cursor /Hugging Face
• Containers: Docker /Kubernetes /Helm /Service Mesh (Istio / Linkerd)
• Databases: PostgreSQL /MongoDB / Redis / Cassandra / Elasticsearch / Pinecone (Vector DB)
• Messaging: Apache Kafka /RabbitMQ /AWS SQS/SNS /Google Pub/Sub
• MLOps & DataOps: MLflow /Kubeflow / SageMaker / Vertex AI /Airflow /dbt
• Observability: Datadog /Prometheus /Grafana /OpenTelemetry / Jaeger /ELK Stack
• CI/CD & IaC: GitHub Actions ArgoCD / Jenkins / Terraform /Ansible /Backstage (IDP)

QUALIFICATIONS & CANDIDATE PROFILE :

Education :

• B.E. / B.Tech or M.E. / M.Tech from a Tier-I or Tier-II Institution - CS, IS, ECE, AI/ML streams strongly preferred
• Demonstrated engineering depth and leadership impact may complement institution pedigree

Experience :

• 10 to 14 years of progressive engineering experience, with at least 3 years in a formal Engineering Manager or equivalent people-leadership role
• Proven track record of managing and scaling engineering teams (615+ engineers) in a fast-growing SaaS or digital product environment
• Hands-on backend engineering background must be able to read, write, and critique production code
• Direct experience driving AI/ML feature delivery or AI tooling adoption within engineering organisations
• Exposure across start-up, mid-size, and large-scale product organisations, preferred adaptability is a core requirement
• Strong CS fundamentals: distributed systems, algorithms, system design, and software architecture
• Demonstrated career stability minimum of 2 years of average tenure per organisation.

The Ideal Engineering Manager in 2026 :

• Leads with context, not control, empowers engineers while maintaining accountability and quality
• Is fluent in both people language and technical language, switches registers naturally with engineers and executives alike
• Sees AI as a force multiplier for the team, not a threat. Actively experiments with and advocates for AI tooling
• Measures success by team outcomes, not personal output. Takes pride in what the team ships, not what they build alone
• Creates feedback loops obsessively between product and engineering, between seniors and juniors, between metrics and decisions
• Has strong opinions, loosely held, brings conviction to discussions but updates on evidence
• Invests in engineering excellence as seriously as delivery velocity knows that quality and speed are not opposites

WHY THIS ROLE STANDS APART :

AI Transformation at Scale :

• Lead one of the most significant AI adoption programmes in India's digital media sector.
• Our decisions will shape how hundreds of engineers work in 2026 and beyond.

Hands-On & Strategic Balance :

• A rare EM role that actively encourages technical depth.
• Stay close to the code while owning the people agenda - the best of both worlds.

Established Platform, Real Scale :

• 5001,000 engineers, proven product-market fit, and the org maturity to execute.
• This is not a greenfield startup gamble it is a serious company with serious ambition.

Clear Leadership Growth Path :

• A visible, direct path toward Director / VP of Engineering.
• Senior leadership is invested in growing its next generation of technology executives.

• Understanding of SDLC & OOPs concepts.

• Must have experience with ASP.NET with C#

• Good knowledge of SQL server / POSTGreSQL database

• Basic Knowledge of javascript, JQuery, CSS, HTML5, Bootstrap

• Ability to design Web architecture.

• Ability to bug fixing in existing projects.

• Knowledge of functions, procedure, triggers.

• Ability to write optimized sql query.

• Good knowledge of developing Desktop Application

• Knowledge of WCF, Web Services and file management.

• Knowledge of digital signature is preferred.

• Should be able to work in a team environment.

• Strong in Software Development and Problem Solving Skills.

• Design, Develop and Unit Test software independently.

• Also should be able to understand the existing applications and should be in position to reengineer the codes to latest .Net technologies.

• Freshers: Should have B.Tech background and should have strong in problem solving skills.

Skills Required :

• Previous Working Experience As A PHP / Laravel Developer For 1-4 Years.
• In-Depth Knowledge Of Object-Oriented PHP And Laravel 5 PHP Framework.
• Hands-On Experience With SQL Schema Design, SOLID Principles, REST API Design, Etc. MySQL Profiling And Query Optimization. Excellent Troubleshooting Skills.
• Good Project Management Skills. Creative And Efficient Problem Solver.

Roles & Responsibilities :

• Build Innovative, State-Of-The-Art Applications And Collaborate With The User Experience (UX) Team. Ensure HTML, CSS, And Shared JavaScript Is Valid And Consistent Across Applications.
• Prepare And Maintain All Applications Utilizing Standard Development Tools.
• Utilize Backend Data Services And Contribute To Increasing Existing Data Services API.
• Coordinate With Co-Developers And Keeps Project Manager Well Informed Of The Status Of Development Effort And Serves As A Liaison Between Development Staff And Project Manager.
• Keep Abreast Of New Trends And Best Practices In Web Development.