Data Delivery Manager at MNC · Kochi (Cochin), trivandrum · 5 - 8 years · ₹25L - ₹32L / yr · Posted 31 Jan 2025

Data Delivery Manager is responsible for managing and overseeing the end-to-end delivery of data
solutions, from data architecture and ingestion to processing, analysis, and reporting. This role
ensures that data projects are completed on time, within scope, and aligned with business
objectives. The Data Delivery Manager works with cross-functional teams, including data
engineers, analysts, and other stakeholders, to deliver high-quality data solutions. Key
Responsibilities: Project and Program Management: o Lead and manage the delivery of data-
driven projects, ensuring they are completed on time and within budget. o Develop and maintain
project plans, timelines, and resource allocation. o Monitor project progress and proactively
identify risks, implementing solutions to ensure successful project completion. o Ensure alignment
between data initiatives and business goals, maintaining continuous communication with
stakeholders. Stakeholder Engagement: o Serve as the primary point of contact between business
stakeholders and the data team, translating business requirements into technical specifications. o
Collaborate with business leaders to understand data needs and develop solutions that meet
those needs. o Provide regular updates on project status, risks, and key deliverables to
stakeholders and leadership teams. o Facilitate meetings to gather requirements and
communicate project milestones. Data Strategy & Architecture: o Oversee the design and
implementation of data solutions that support business objectives. o Ensure adherence to data
governance and quality standards throughout the data pipeline lifecycle. o Collaborate with data
architects to define scalable, secure, and high-performance data architectures. o Support data
integration initiatives across different platforms, ensuring smooth and efficient data flow. Team
Leadership and Development: o Manage cross-functional teams of data engineers, analysts, and
other professionals to deliver projects effectively. o Provide leadership and mentoring to team
members, fostering a culture of collaboration, innovation, and continuous learning. o Set clear
expectations, performance goals, and career development opportunities for the team. o Address
and resolve any team challenges, ensuring high levels of productivity and motivation. Quality
Assurance: o Ensure the accuracy, reliability, and quality of data solutions by implementing robust
testing, validation, and review processes. o Develop and enforce data standards, best practices,
and methodologies to ensure consistent, high-quality deliverables. o Drive continuous
improvement initiatives, analyzing past projects and identifying areas for enhancement. Risk
Management and Troubleshooting: o Identify potential risks to project delivery, including data
pipeline issues, resource shortages, or technical blockers, and implement mitigation strategies. o
Troubleshoot and resolve data-related issues and challenges during the project lifecycle.
Reporting and Analytics: o Oversee the creation and maintenance of data dashboards, reports, and
performance metrics. o Ensure that data solutions provide actionable insights for the business,
driving informed decision-making. Experience: o 5+ years of experience in managing programs
related to data management, data engineering, or analytics. o Proven track record in managing
data projects and delivering data solutions in a timely manner. o Experience with data integration,
data warehousing, and data modeling. o Strong understanding of data pipeline management, ETL
processes, and data analytics. Skills: o In-depth knowledge of data management tools and
technologies (e.g., SQL, NoSQL, ETL tools, cloud platforms such as AWS, Google Cloud, or Azure).
o Proficient in project management methodologies (Agile, Scrum, Waterfall). o Strong leadership
and team management skills, with the ability to drive collaboration across different functions. o
Excellent communication skills with the ability to translate complex data-related concepts into
understandable terms for non-technical stakeholders. o Analytical mindset with strong problem-
solving abilities. o Knowledge of data visualization and reporting tools (e.g., Power BI, Tableau,
Looker) is a plus. Certifications: o Project Management Professional (PMP) or Scrum Master
certification (preferred). o Data-related certifications (e.g., AWS Certified Big Data, Google
Professional Data Engineer) are a plus. Preferred Skills: o Experience with big data technologies
(e.g., Hadoop, Spark, Kafka). o Familiarity with machine learning or AI applications related to data
solutions. o Experience with data governance and compliance (e.g., GDPR).

Similar jobs (10)
Hiring for Data Engineer - Delivery Manager
Exp : 10 - 15 yrs
Edu : BE/B.Tech/MCA
Work Loation : Hyderabad
.Roles & Responsibilitie:
Own end-to-end delivery of data engineering programs ensuring alignment with business goals, timelines, and quality standards.
Drive execution across multiple data initiatives within Azure and Databricks environments.
Provide technical leadership in designing and implementing scalable data pipelines using Python, PySpark, and Spark.
Required Skills:
Strong experience with Databricks, PySpark, Python, and Spark.
Expertise in Azure Data Services including ADF, ADLS, and Synapse.
Proven experience in delivery management, stakeholder management, and Agile execution
15+ years of IT Delivery and Technology Services experience.
15+ years managing large offshore delivery organizations.
Proven leadership of portfolios exceeding 200+ resources.
Financial Services or Banking experience is a MUST
Extensive technical experience in Data Engineering, Data Platforms, Data Brics.
Cloud Data Transformation Programs, Data Warehousing, Azure Data Platform and compliance experience
Technical Lead
Job Description
Role Overview
We are seeking a highly skilled Data Engineering Lead with minimum of 5 years of hands-on experience in Azure data engineering, data warehousing, and automation-driven integration. The ideal candidate should be a proven technical lead, capable of driving end-to-end
project delivery and working closely with customer teams. This is a Work from Office / Customer Site role.
Roles and Responsibilities
• Lead the design, development, and delivery of data engineering and automation projects.
• Architect and implement ETL/ELT pipelines using Azure Data Factory.
• Design and manage enterprise data warehouses including dimensional modeling and
schema optimization.
• Manage Azure components including Storage Accounts, Data Lakes, Azure SQL, and Synapse.
• Drive automation initiatives across data ingestion and transformation workflows.
• Collaborate with business and technical stakeholders to translate requirements into scalable solutions.
• Mentor team members and enforce engineering best practices.
• Serve as the technical anchor responsible for ensuring high-quality, on-time delivery.
Skills and Qualification
• Strong hands-on experience with Azure Data Factory, Azure Storage, Azure SQL/Synapse.
• Deep understanding of data warehousing concepts: star/snowflake schemas, fact/dimension modeling.
• Experience with automation-led data engineering solutions.
• Strong troubleshooting, optimization, and analytical skills.
• Excellent communication and stakeholder management abilities.
• Proven experience as a Technical Lead leading teams and delivery.
Must Have
• Min of 5 years of relevant data engineering experience.
• Strong Azure Data Engineering and Data Warehousing expertise.
• Proven Technical Lead experience.
• Ability to work from office and customer site.
• Strong ownership mindset with a focus on quality and delivery excellence.
Job Summary
Role Overview
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.
Experience with Google Cloud Platform (GCP) will be an added advantage.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
- Develop complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain reliable data integration workflows across multiple data sources.
- Perform data cleansing, validation, transformation, and quality checks.
- Analyze data and provide insights to support business and technical requirements.
- Implement and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
- Troubleshoot data pipeline failures, performance issues, and production incidents.
- Optimize data processing workflows for performance, scalability, and reliability.
- Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
- Follow best practices for version control, testing, documentation, and deployment.
- Contribute to cloud-based data engineering initiatives, preferably on GCP.
Required Skills
- 5–7 years of hands-on experience in Data Engineering.
- Strong programming skills in Python.
- Strong expertise in Advanced SQL and database concepts.
- Hands-on experience with ETL/ELT processes and data pipelines.
- Good understanding of Data Warehousing and Data Modeling concepts.
- Experience with CI/CD practices and tools.
- Strong understanding of DevOps principles, automation, and deployment processes.
- Strong data analytics and problem-solving skills.
- Experience working with large datasets and performance optimization.
- Good understanding of Git/version control and software development best practices.
Good to Have
- Hands-on experience with Google Cloud Platform (GCP).
- Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
- Experience with containerization/orchestration technologies such as Docker/Kubernetes.
- Experience with workflow orchestration tools such as Airflow.
- Knowledge of cloud-based data architecture and distributed data processing.
Preferred Candidate Profile
- Strong analytical and problem-solving abilities.
- Good communication and stakeholder management skills.
- Ability to work independently as well as in a collaborative team environment.
- Strong ownership of data pipelines and production systems.
- Candidates who can join at short notice are preferred.
Mandatory Skills
Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops
Job Summary
The Technical Lead will be responsible for overseeing and leading projects related to Azure Data Factory (ADF), Azure Databricks, SQL, Oracle PL/SQL, and Python. The role involves designing, developing, and implementing data solutions while ensuring they meet the business requirements and align with best practices. (1.) Key Responsibilities
1. Lead and manage end-to-end data engineering projects using azure data factory, azure databricks, sql, oracle pl/sql, and python.
2. Collaborate with stakeholders to gather and understand requirements for data pipelines and analytics solutions.
3. Design and develop etl processes, data models, and data integration solutions.
4. Provide technical guidance and mentorship to the team members.
5. Ensure data quality, data governance, and data security standards are maintained throughout the project lifecycle.
6. Troubleshoot and optimize data pipelines and processes for performance and efficiency.
7. Stay updated on the latest trends and technologies in data engineering and contribute to continuous improvement efforts.
Skill Requirements
1. Proficiency in azure data factory (adf) and azure databricks for building and managing data pipelines.
2. Strong experience with sql and oracle pl/sql for data querying and manipulation.
3. Advanced programming skills in python for scripting and data processing tasks.
4. Knowledge of data modeling, data warehousing concepts, and database design principles.
5. Ability to work in a collaborative team environment and communicate effectively with stakeholders.
6. Strong analytical and problem-solving skills with attention to detail.
7. Experience in data visualization tools and techniques is a plus.
Certifications: Relevant certifications in Azure Data Factory, Azure Databricks, SQL, Oracle PL/SQL, or Python are advantageous.
Skill (Primary)
Data Fabric-Azure-Azure Data Factory (ADF)
We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.
Qualifications and Skills:
- Minimum 5 years of experience as a Data Engineer
- Hands-on experience with Azure cloud-based data solutions
- Expertise in database design and management, including SQL databases such as SQL Server
- Proficient in ETL (Extract, Transform, Load) design for data integration and processing
- Strong knowledge of data modeling principles and techniques
- Ability to analyze and translate data into actionable insights, reports, and visualizations
- Proficiency in Power BI for reporting and data visualization
Desirable Skills:
- Experience with Power BI Report Builder / Reporting Services
- Knowledge of statistical analysis or Data Science
- Experience within the UK Insurance industry is a plus
- Python or R coding skills
Responsibilities:
- Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
- Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
- Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
- Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
- Implement different methods of streaming data and create reconciliations for datasets
- Build analytical models to support reporting and analytics
- Collaborate with an agile delivery team to work on the backlog of specified work
About Us:
The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
Job Summary:
We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.
As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.
Key Responsibilities:
- Design, develop, test, and maintain optimal data pipeline and ETL architectures.
- Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
- Prepare and optimize data for predictive and prescriptive modeling.
- Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
- Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
- Utilize big data tools and frameworks to optimize data acquisition and preparation.
- Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
- Develop and curate data models for analytics, dashboards, and reports.
- Conduct code reviews, maintain production-level code, and implement testing approaches.
- Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
- Drive innovation and implement efficient new approaches to data engineering tasks.
Must-Have Skills:
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
- 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
- 3–5 years of experience designing and implementing data warehouse solutions.
- Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
- Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
- Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
- Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
- Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
- Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
- Strong problem-solving, communication, and collaboration skills.
Good-to-Have Skills:
- Experience in integrating ERP data into data lakes.
- Experience with traditional ETL tools (e.g., Talend, Pentaho).
Competencies:
- Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
- Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
- Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
- Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
Why Join Us?
- Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
- Work on impactful projects that make a difference across industries.
- Opportunities for professional growth and continuous learning.
- Competitive salary and benefits package.
Application Details
Ready to make an impact? Apply today and become part of the QX Impact team!
GEMBA CONCEPTS · TECHNOLOGY DIVISION
· JOB DESCRIPTION
Technical Delivery Manager – Services LOCATION Bengaluru (Hybrid) ABOUT GEMBA CONCEPTS EXPERIENCE 5–8 years REPORTS TO Chief Technology Officer TYPE Full-time Gemba Concepts helps manufacturers and enterprises improve how their operations run. Our technology division builds and runs Gemba Connect, a suite of enterprise SaaS products spanning warehouse management, logistics, ERP, and applied AI/ML, deployed across 30+ active client accounts in manufacturing, pharma, FMCG and retail.
ABOUT THE ROLE
We're looking for a technical leader to own Gemba's services business end to end: delivery, people, commercials and reporting. You'll run every client implementation and custom development engagement, build and manage the team that delivers them, and be the single point of accountability to clients and leadership for how services perform. You've written production Java code, can read a Spring Boot service and a SQL execution plan, and have since hired, reviewed and led delivery teams. The product roadmap stays with product leadership; everything we deliver to clients runs through you.
WHAT YOU'LL OWN Services business ownership
• Own the health of the services portfolio: delivery, client satisfaction, billing milestones and account growth.
• Run post-sale SOW execution. Ensure milestones are hit and billed on time, and follow up with finance and clients on receivables.
• Grow accounts by converting change requests and enhancements into scoped, priced, billable work.
• Track effort, utilisation and margin by account; act when an engagement turns unprofitable. Delivery
• Run multiple concurrent client implementations, owning scope, timeline, cost and quality.
• Plan and run sprints with Tech Leads: grooming, estimation, capacity planning, reviews and retros.
• Own go-lives (UAT, cutover, data migration, hypercare) and post-go-live support SLAs.
• Maintain RAID logs and delivery dashboards; flag risk early, with a proposed fix. Requirements and change control
• Be the single intake point between consulting teams, clients and engineering; convert requirements into user stories with testable acceptance criteria.
• Baseline scope and run a formal change-request process. Every change is priced in effort, cost and date before it's accepted.
• Make sure what's agreed is documented before it's built. People and hiring • Plan services headcount against the delivery pipeline and run hiring end to end (role definition, interviews, closing) at a high bar.
• Run goal-setting, regular 1:1s and performance reviews for the services team; give input on promotions, compensation and performance plans.
• Grow Tech Leads and senior engineers into people who can own accounts independently.
• Own team retention and morale. Know who's at risk before they resign. Gemba Concepts · Technology Division Page 1GEMBA CONCEPTS · TECHNICAL DELIVERY MANAGER – SERVICES Reporting
• Publish monthly services MIS to leadership: revenue billed, collections, on-time delivery, SLA adherence, utilisation, hiring and attrition.
• Contribute the services section to quarterly board reporting.
• Run monthly or quarterly business reviews with key client stakeholders. Technical oversight
• Work with Tech Leads on design reviews, integrations (ERP, WMS, third-party systems) and non-functional requirements.
• Lead incident triage and root-cause reviews on client escalations; track corrective actions to closure.
• Coordinate with DevOps on environments, CI/CD and release windows.
• Uphold security and compliance controls (e.g., SOC 2) across delivery. Improving how we deliver
• Drive adoption of AI-assisted development and testing tools, and measure whether they actually raise throughput per engineer.
• Tighten estimation accuracy, definition of done and release discipline across the services team. MUST-HAVES
• 5–8 years in software, including 2+ years as a hands-on Java developer and 2+ years in delivery or project management.
• 1+ year leading a team of 5+ directly, including hiring and performance reviews.
• Strong working knowledge of Java and Spring Boot. You can review a PR, understand how a service is structured, and challenge an estimate.
• Solid SQL: schema design, writing and debugging queries, and understanding of indexing, transactions and production issues such as slow queries and connection pool exhaustion (SQL Server/Azure SQL, PostgreSQL or MySQL).
• Hands-on exposure to cloud platforms (Azure preferred, AWS/GCP acceptable).
• Working experience with the commercial side of client engagements: SOWs, milestone billing and change orders. Margin tracking is a plus.
• Track record of delivering enterprise B2B software to external clients across multiple parallel engagements.
• Proficiency with Jira or Azure DevOps, Confluence and Git-based workflows.
• Clear communication. You can present to a client CXO, write a board-ready MIS, and give an engineer hard feedback. GOOD TO HAVE
• Domain experience in manufacturing, supply chain, warehousing, logistics or ERP.
• Background in an IT services firm or the services arm of a product company.
• Familiarity with microservices, REST API design and message queues.
• Experience delivering AI/ML features.
• Exposure to SOC 2 or ISO 27001 audits.
• Certifications (PMP, CSM, PMI-ACP) are welcome but won't substitute for a delivery and team-building track record. WHAT SUCCESS LOOKS LIKE IN YOUR FIRST 6 MONTHS
• 85%+ of implementations go live on the committed date.
• Billing milestones are invoiced on time, and receivables ageing is visibly down. • Every active account has baselined scope, a live RAID log and a change log.
• Services hiring is on plan, with near-zero regretted attrition.
• Leadership gets a monthly services MIS without having to chase it. WHO YOU'LL WORK WITH The services delivery team (engineers, Tech Leads, BAs, QA), product squads, DevOps, consulting teams, finance and client stakeholders.
WHY JOIN Own a real business line with direct access to leadership. Build the team and operating model your way. Work on enterprise products in active growth, including applied AI.
Strong Senior Project Manager Profile with enterprise B2B SaaS, client-facing delivery experience
2
Mandatory (Experience 1): Must have 5+ years of project management experience with significant client-facing delivery time (non-negotiable), including experience in a B2B SaaS company serving enterprise customers
3
Mandatory (Experience 2): Must have managed complex enterprise projects end-to-end, from requirement/planning through successful delivery and go-live
4
Mandatory (Experience 3): Must have managed multi-country / multi-region rollouts (preferably North America and/or Europe), coordinating India-based delivery teams with customers/stakeholders in Western markets
5
Mandatory (Experience 4): Must have delivered technically complex / analytics-driven projects (AI/ML, Image Recognition, or Data Analytics)
6
Mandatory (Tech skill): Must have strong working knowledge of SQL, APIs, and Master Data Management (MDM)
7
Mandatory (Experience 5): Must have experience with SOWs, change requests, or RFPs, managing scope, timelines, risks, and dependencies using Waterfall or Agile
8
Mandatory (Ownership): Must be the accountable owner of the engagement — primary client point of contact, owning the project plan and go-live end-to-end — not a hands-on specialist executing the build
9
Mandatory (Skill): Must have strong facilitation, communication, stakeholder-management, and executive-level reporting skills across cross-functional, geographically distributed teams
10
Mandatory (Note): CTC is inclusive of variable
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Preferred (Experience): Prior experience with customer onboarding
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Preferred (Certification): PMP, CAPM, ITIL, or CSM.
Role Overview
We are looking for a GCP Data Engineer with 10+ years of experience to design, develop, and optimize scalable cloud-based data solutions. The ideal candidate will have strong hands-on expertise in GCP, BigQuery, and advanced SQL, with experience building data pipelines and working with large-scale datasets.
Key Responsibilities
- Design and develop scalable data pipelines and ETL/ELT processes on GCP.
- Build, optimize, and maintain data solutions using Google BigQuery.
- Develop complex SQL queries for data transformation, aggregation, and analysis.
- Design efficient data models and optimize pipelines for performance, scalability, and cost.
- Integrate data from multiple sources and ensure data quality, reliability, and availability.
- Troubleshoot pipeline and data issues and drive continuous improvement.
- Collaborate with data architects, analysts, application teams, and business stakeholders.
- Follow best practices for cloud security, data governance, testing, and documentation.
Required Skills
- 8+ years of Data Engineering experience
- Strong hands-on experience with GCP, Django, and MongoDB
- Extensive experience with BigQuery
- Advanced SQL skills
- Strong understanding of ETL/ELT and data pipeline development
- Data modeling and data warehousing experience
- Experience handling large-scale datasets and performance optimization
- Strong problem-solving and communication skills
Good to Have
- GCP services such as Cloud Storage, Dataflow, Pub/Sub, Cloud Composer, or Cloud Functions
- Python or other data engineering languages
- Experience with data governance and security
- Agile development experience













