Warehouse Manager Jobs in Chennai.
All active Warehouse Manager roles based in Chennai.
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About Tekion:
Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.
Job Description
We’re seeking a hands-on Senior Data Architect to design and modernize scalable, AI-ready data platforms across cloud. The ideal candidate has deep technical expertise in AWS, PySpark, and Python, and experience migrating legacy Java-based scripts to Spark frameworks while ensuring data quality, scalability, and performance.
Key Responsibilities
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Design and implement data architecture and pipelines using PySpark, Python, and AWS services (Glue, EMR, S3, Redshift, Athena).
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Modernize legacy systems by converting Java-based migration or ETL scripts into Spark-based solutions.
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Build and manage data lakes and data warehouses optimized for analytics and AI/ML workflows.
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Collaborate with data scientists and analysts to enable model training, deployment, and continuous data delivery.
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Define and document HLD (High-Level Design) and LLD (Low-Level Design) for scalable data systems.
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Implement standards for data quality, governance, performance optimization, and security.
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Lead troubleshooting, performance tuning, and architecture reviews for data pipelines.
Skills and Experience
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15+ years of experience in data engineering or architecture, with strong hands-on development background.
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Expert-level proficiency in PySpark, Python, and SQL for data processing and transformation.
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Strong understanding of AWS data ecosystem — including Glue, EMR, S3, Redshift, and Lambda.
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Proven experience migrating or re-engineering Java-based ETL systems into modern Spark environments.
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Solid foundation in data lake, data warehouse, and cloud-native architecture design.
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Experience supporting AI/ML data pipelines and integrating data platforms with ML workflows.
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Strong documentation skills (HLD, LLD) and ability to communicate architecture clearly to technical and business stakeholders.
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Experience with both RDBMS such as Maria DB/MySQL and No-SQL database such MongoDB
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Experience with GIT, Jenkins, & AWS
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Expertise in performance optimization and cost management for cloud environments
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Ability to manage multiple projects and priorities in a fast-paced environment
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AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional
Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.
For more information on our privacy practices, please refer to our Applicant Privacy Notice here.
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Apply to Tekion
Critically, this role sits at the intersection of data, AI, and people. The ideal candidate will be as comfortable enabling a frontline sales rep to understand and act on a dashboard as they are presenting strategic insight to a C-suite audience. They will also be a confident and curious adopter of large language model (LLM) tools — using AI to accelerate their own analytical workflow and helping the wider business do the same.
Key Responsibilities
- Business Analysis & Stakeholder Partnership
- Act as the primary analytics partner to senior commercial stakeholders across Sales, Marketing, Customer Success, and Revenue Operations.
- Apply strong business analysis discipline — translating ambiguous business questions into well-scoped requirements, clear success criteria, and structured analytical briefs before any build begins.
- Proactively surface insights, trends, risks, and opportunities that inform decision-making at leadership level.
- Support strategic initiatives such as CRM consolidation, demand intelligence optimization, territory and book-of-business changes, and forecasting improvements.
- Own end-to-end project management of analytics deliverables — from requirements gathering and prioritization through to delivery, adoption, and iteration — ensuring stakeholders are informed and timelines are met
- Communication, Enablement & Influence
- Demonstrate exceptionally strong communication skills across all levels of the organisation — from crafting executive narratives for senior leadership forums to running hands-on enablement sessions for managers and frontline sales representatives.
- Translate complex data, AI outputs, and analytical findings into plain-language stories that drive clarity, confidence, and action.
- Design and deliver enablement programmes that help managers and reps understand, trust, and act on dashboards, KPIs, and AI-generated insights — building genuine data literacy across the Revenue Organisation rather than dependency on the BI team.
- Champion clear, consistent communication of what metrics mean, how they are calculated, and why they matter — removing ambiguity at every level.
- Influence without authority; build credibility with senior stakeholders through the quality of insight and the integrity of the underlying data.
- Analytics, Reporting & Insight
- Own the design and delivery of executive-level dashboards and self-service reporting, primarily using Power BI.
- Ensure consistent definitions and calculations for revenue KPIs, North Star metrics, and commercial performance indicators.
- Conduct deep-dive analyses to diagnose performance issues and recommend actionable next steps.
- Write and optimise advanced SQL queries to extract, transform, and validate data across our Databricks data warehouse and connected source systems.
- Leverage Databricks as the central analytical platform — working within notebooks, SQL warehouses, and the broader Lakehouse environment to build reliable, scalable analytical outputs.
- AI & LLM Integration
- Be a power user and internal advocate of LLM-based tools, including Microsoft Copilot and Anthropic Claude (including Claude Code), using them to accelerate analysis, generate and review SQL, draft communications, and surface insight more efficiently.
- Help define and create LLM agents for the Go To Market organisation – connecting context to frontline AI tools such as MS Copilot and Salesloft.
- Proactively identify opportunities to embed LLM and AI capabilities into BI workflows, dashboards, and analytical processes — raising the ceiling of what the team can deliver.
- Work with the Senior Manager of BI to evaluate and scale AI-assisted analytics approaches across the team, including the use of Databricks' native LLM and AI capabilities.
- Help commercial stakeholders and frontline teams understand and appropriately trust AI-generated outputs — building confidence in AI tools through clear explanation, demonstration, and enablement.
- Data Modelling & Quality
- Partner with Data Analytics Engineers to define analytical data models that support revenue, pipeline, customer lifecycle, and performance reporting.
- Validate data accuracy and integrity across the analytics layer, proactively identifying and resolving issues before they impact decision-making.
- Contribute to data governance standards, metric documentation, and reporting best practices.
- Technology & Tooling Context
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- The Lead Business Analyst will work within a modern BI and revenue intelligence stack, including:
- Layer Tools
- Data Warehouse & Analytics Databricks (central data warehouse with LLM capabilities)
- BI & Visualisation Power BI
- AI & LLM Tooling Microsoft Copilot, Anthropic Claude, Claude Code, Databrick Genie, Databricks hosted LLM models
- Core Commercial Systems Salesforce (multiple instance), PlanHat, &
- Revenue & Demand
- Intelligence Clay
- Sales Enablement &
- Engagement Salesloft (including AI and conversational intelligence) & HighSpot
- A strong understanding of how these systems connect — and how data flows end-to-end from source systems to executive dashboards and frontline tools — is essential.
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- Required Experience & Skills
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- 8+ years of experience in a Business Analysis, Analytics, or BI within a SaaS or technology-driven organisation.
- Experience supporting RevOps, Sales Operations, or Commercial Analytics teams.
- Advanced SQL skills — comfortable writing complex queries, debugging data issues, and working directly within a cloud data warehouse environment; Databricks experience strongly preferred.
- Strong business analysis capability — proven ability to scope, structure, and document analytical requirements with rigour before moving into delivery.
- Proven project management skills — able to manage multiple concurrent workstreams, set and meet deadlines, and maintain clear stakeholder communication throughout.
- Exceptionally strong communication skills — a natural and compelling communicator in written and verbal form, equally effective presenting strategy to a VP as running a training session for a team of account executives.
- Demonstrated experience designing and delivering stakeholder enablement on data, dashboards, or analytics tooling — not just building outputs, but ensuring they are understood and adopted.
- Proven experience delivering executive-ready dashboards and self-service reporting (Power BI preferred).
- Strong commercial and revenue-focused business acumen.
- Active and confident user of LLM tools such as Microsoft Copilot or Anthropic Claude in a professional analytical context.
- Preferred Experience
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- Hands-on experience with Databricks — including SQL warehouses, notebooks, and the Lakehouse architecture.
- Experience using Claude Code or similar AI coding assistants to accelerate SQL development, data validation, or analytical scripting.
- Familiarity with CRM and GTM analytics — Salesforce, pipeline reporting, forecasting, MEDDPICC, territory models.
- Hands-on Experience with Clay
- Ideally experience with Python (e.g. connecting to APIs)
- Exposure to building or scaling data literacy programmes within a commercial organisation.
- What Success Looks Like
- Leaders trust the dashboards and insights/recommendations produced and use them to run the business with confidence.
- Managers and frontline reps understand and act on data, insights, and AI outputs — because this role has invested in enabling them, not just building for them.
- KPIs and metrics are clearly defined, consistently applied, and widely adopted across the organisation.
- LLM and AI tools are meaningfully embedded into BI workflows, improving speed, quality, and reach of analytical output.
- The BI team is seen as a strategic partner — not just a reporting function.
- Data quality issues are proactively identified and resolved before impacting decision-making.
- Projects are delivered on time, with clear communication and minimal surprises for stakeholders.
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Apply to Cision
Applied AI Engineer - MCP
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Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you’ll be part of a passionate team dedicated to accomplishing hard things, together.
About the Team At Business Technology, we use Appian to run Appian. We are launching our first internal AI team to build the foundation for how our global company works. This team won't just use AI, they will build the brain of the enterprise, spanning everything from predictive intelligence in our data warehouse to the GenAI infrastructure that powers our internal autonomous agents.
We are hiring a founding group of engineers to kickstart this mission. As an AI Engineer on this team, you won’t be maintaining legacy systems; you’ll be building from the ground up. You will own the full spectrum of AI: crafting predictive ML models to find insights in our data warehouse and architecting GenAI systems that allow any employee to interact with enterprise knowledge through intelligent agents.
If you want to be part of the original team that defines internal AI for a leading automation company, this is your moment.
PLEASE NOTE: This is a midlevel role and is aimed at people with 3+ years experience
What you’ll do:
- Build the AI Platform: Design, deploy, and scale GenAI infrastructure on GCP Vertex AI (preferred) or AWS Bedrock.
- Build & Operate MCP Servers: Develop and maintain Model Context Protocol (MCP) servers that expose enterprise systems (databases, APIs, internal tools) as structured, AI-consumable capabilities.
- Design the Tool Layer: Build the tool registry and invocation framework that allows agents to interact with internal systems safely and reliably including schema design, access controls, and error handling.
- Engineer Agent-to-Agent Infrastructure: Architect the communication and coordination layer that allows specialized agents to delegate tasks, share context, and compose into larger autonomous workflows.
- Own the Retrieval Layer: Architect and operate RAG systems, including vector stores, embedding pipelines, chunking strategies, and retrieval evaluation frameworks.
- Establish AI Reliability: Instrument AI systems with logging, tracing, latency monitoring, and evaluation hooks so agents can be trusted, debugged, and improved in production.
Required Qualifications:
- AI Infrastructure Experience: Professional experience building and deploying production-grade GenAI systems on GCP Vertex AI or AWS Bedrock including LLM APIs, agent frameworks, and RAG pipelines.
- Python Mastery: Deep proficiency in Python and common AI/ML libraries (e.g., LangChain, LlamaIndex, OpenAI SDK, Google Cloud AI SDK).
- Agentic Systems: Hands-on experience building multi-step, tool-calling AI agents that operate reliably in production including tool schema design, structured outputs, and failure handling.
- MCP or Tool Protocol Experience: Familiarity with Model Context Protocol (MCP) or equivalent patterns for exposing enterprise resources to AI systems as callable, permissioned tools.
- Vector & Retrieval Systems: Experience with vector databases (Pinecone, pgvector, or similar) and embedding-based retrieval at scale.
- Technical Foundation: B.S. in Computer Science, Engineering, or a related technical field.
- The Pioneer Mindset: A self-starter who is excited to be part of a "first-of-its-kind" team and thrives in environments where you are building the playbook.
Preferred Qualifications:
- Multi-Agent Architectures: Experience designing orchestrator/subagent patterns, agent handoff protocols, or systems where multiple AI models coordinate to complete complex tasks (e.g., using frameworks like LangGraph, CrewAI, or AutoGen).
- AI Observability: Experience with LLM evaluation frameworks, prompt regression testing, or agent trace monitoring (e.g. custom eval pipelines).
- Data Warehouse Integration: Familiarity with SQL and pulling data from Snowflake or BigQuery to ground AI agents in live business context.
- Appian Exposure: Experience with the Appian platform or interest in integrating AI agents into low-code automation workflows.
- Predictive ML (Nice to Have): Some familiarity with ML fundamentals is a plus, but not a focus of this role.
This role is based at our Chennai office in Brigade World Trade Center Chennai. Appian was built on a culture of in-person collaboration, which we believe is a key driver of our mission to be the best. Employees hired for this position are expected to be in the office 5 days a week to foster that culture and ensure we continue to thrive through shared ideas and teamwork. We believe being in the office provides more opportunities to come together and celebrate working with the exceptional people across Appian.
Tools and Resources
- Training and Development: During onboarding, we focus on equipping new hires with the skills and knowledge for success through department-specific training. Continuous learning is a central focus at Appian, with dedicated mentorship and the First-Friend program being widely utilized resources for new hires.
- Growth Opportunities: Appian provides a diverse array of growth and development opportunities, including our leadership program tailored for new and aspiring managers, a comprehensive library of specialized department training through Appian University, skills based training, and tuition reimbursement for those aiming to advance their education. This commitment ensures that employees have access to a holistic range of development opportunities.
- Community: We’ll immerse you into our community rooted in respect starting on day one. Appian fosters inclusivity through our 8 employee-led affinity groups. These groups help employees build stronger internal and external networks by planning social, educational, and outreach activities to connect with Appianites and larger initiatives throughout the company.
Benefits
Appian offers a comprehensive benefits package designed to support your health, wellbeing, and financial future. Benefits may include health coverage, Employee Assistance Program (EAP) with free mental health support, life and disability insurance, an Employee Stock Purchase Program (ESPP), a retirement/pension plan, wellness dollars, tuition reimbursement, family-forming benefits and more. Benefits vary by country—please ask your Talent Acquisition contact for details specific to the location you are applying to.
About Appian
Appian provides process automation technology. We automate complex processes in large enterprises and governments. Our platform is known for its unique reliability and scale. We’ve been automating processes for 25 years and understand enterprise operations like no one else. For more information, visit appian.com. [Nasdaq: APPN]
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Appian is an equal opportunity employer that strives to attract and retain the best talent. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state, or local law.
Appian provides reasonable accommodations to applicants in accordance with all applicable laws. If you need a reasonable accommodation for any part of the employment process, please contact us by email at ReasonableAccommodations@appian.com. Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address.
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Apply to Appian CorporationTechnical Lead (MS Fabric, Databricks and Snowflake)
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Job Overview:
We are looking for a senior technical lead to design, scale, and govern enterprise-grade data platforms across Microsoft Fabric, Databricks, and Snowflake. The role focuses on defining data architecture standards, enabling AI/GenAI-ready platforms, leading engineering teams, and delivering secure, high-performance cloud data solutions that support analytics and business outcomes.
Key Responsibilities
- Lead the design and implementation of scalable data platforms using Microsoft Fabric, Databricks and Snowflake including Pipelines, Notebooks, Lakehouse, Data Warehouse, and Semantic Models.
- Define end-to-end data architecture standards, patterns, and best practices across ingestion, storage, transformation, modeling, and consumption layers.
- Guide technical decisions on compute patterns, storage optimization, pipeline orchestration, and data modeling frameworks.
- Evaluate and integrate emerging technologies to modernize the platform and enable AI/GenAI workloads.
- Partner with AI/ML teams to productionize models and integrate them with enterprise data workflows.
- Ensure data governance, lineage tracking, and metadata standards to support trustworthy AI initiatives.
- Champion data governance, security, privacy, and compliance requirements within the platform.
- Implement observability frameworks for pipeline monitoring, performance tuning, and reliability engineering.
- Drive continuous improvement initiatives to enhance platform robustness and engineering productivity.
- Work closely with product owners, business stakeholders, architects, and analytics teams to translate requirements into scalable technical solutions.
- Serve as the primary technical point of contact for data platform projects and stakeholders.
- Communicate technical roadmaps, project risks, and delivery plans clearly and effectively.
- Develop and deliver dashboards and reports using Power BI and Tableau.
Key Skills:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or equivalent professional experience.
- 12+ years of experience in data engineering, data platform development, or cloud data architecture.
- 3+ years in a technical leadership or team management role.
- Mandatory deep hands-on expertise with Microsoft Fabric, Snowflake or Databricks:
- Pipelines
- Notebooks
- Lakehouse
- Data Warehouse
- Semantic Models
- Strong proficiency in PySpark, distributed compute, and data transformation frameworks.
- Advanced SQL capabilities and experience building stored procedures for transactional and analytical workloads.
- Proven track record in designing and delivering large-scale data platforms in cloud environments (Azure preferred).
- Solid understanding of AI/ML data workflows, GenAI dataset preparation, and integration patterns.
- Demonstrated ability to lead engineering teams, drive architectural decisions, and oversee complex technology implementations.
- Strong communication, stakeholder management, and technical documentation skills.
- Proficiency in creating interactive dashboards and reports using Power BI and Tableau.
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Apply to Orion Innovation Naukri
Senior Data Engineer (Fabric and Databricks)
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Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.
Job Overview:
We are seeking an experienced Senior Data Engineer to build and optimize scalable data platforms using Microsoft Fabric, Databricks (and/or Snowflake). The role focuses on designing reliable data pipelines, lakehouse and warehouse models, and semantic layers that enable enterprise analytics, BI, and AI/Gen AI use cases.
You will work closely with analytics, BI, and data science teams to deliver high-quality, performant, and governed data solutions, while driving best practices in data engineering, optimization, and platform design.
Key Responsibilities
- Design, build, and maintain end-to-end data solutions on Microsoft Fabric, Databricks, including Pipelines, Notebooks, Lakehouse, Data Warehouse, and Semantic Models.
- Implement scalable data ingestion, transformation, and loading (ETL/ELT) using Fabric Pipelines and PySpark.
- Develop robust data models and schemas optimized for analytics, reporting, and AI-driven consumption.
- Create and maintain semantic models to support Power BI and enterprise BI solutions.
- Engineer high-performance data solutions that meet requirements for throughput, scalability, quality, and security.
- Author efficient PySpark and SQL code for large-scale data transformation, data quality management, and business rule processing.
- Build reusable framework components for metadata-driven pipelines and automation.
- Optimize Lakehouse and Data Warehouse performance, including partitioning, indexing, Delta optimization, and compute tuning.
- Develop and maintain stored procedures and advanced SQL logic for operational workloads.
- Design and prepare feature-ready datasets for AI and GenAI applications.
- Collaborate with data scientists and ML engineers to productionize AI pipelines.
- Implement data governance and metadata practices required for responsible AI.
- Leverage Fabric, Databricks capabilities to orchestrate and monitor AI-related data workflows.
- Apply data governance, privacy, and security standards across all engineered assets.
- Implement monitoring, alerting, and observability best practices for pipelines and compute workloads.
- Drive data quality initiatives, including validation frameworks, profiling, and anomaly detection.
- Partner with analytics, BI, data science, and product teams to understand requirements and translate them into technical solutions.
- Mentor junior engineers and contribute to engineering standards and patterns.
- Participate in architecture reviews, technical design sessions, and roadmap planning.
- Develop and deliver dashboards and reports using Power BI and Tableau.
Required Skills:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or equivalent experience.
- 7+ years of professional experience in data engineering or a related discipline.
- Mandatory hands-on expertise with Microsoft Fabric, Databricks or Snowflake including:
- Pipelines
- Notebooks
- Lakehouse
- Data Warehouse
- Semantic Models
- Advanced proficiency in PySpark for distributed data processing.
- Strong command of SQL for analytical and operational workloads.
- Experience developing and optimizing stored procedures and complex SQL transformations.
- Understanding of GenAI architectures, vectorization, embedding pipelines, and data preparation for LLM use cases.
- Strong knowledge of data modeling, ETL/ELT patterns, and modern data lakehouse principles.
- Experience designing and optimizing large-scale data pipelines in cloud environments (Azure preferred).
- Excellent problem-solving skills with the ability to analyze complex data workflows.
- Proficiency in creating interactive dashboards and reports using Power BI and Tableau.
Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
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