Data Engineer/Analyst – Python, Spark, SQL, Cloud & Data Architecture

Overview

Lead Data and Analytics projects and deliver data-driven solutions combining data engineering, analytics, data architecture, modeling, integration, visualization, governance, project delivery, and team leadership.

What you'll do

• Lead and manage Data and Analytics projects from requirements definition through delivery and transition.
• Work with clients and internal stakeholders to understand business requirements and develop data-driven solutions.
• Provide technical expertise and guidance to junior team members and project teams.
• Oversee data collection, cleansing, transformation, validation, and preparation processes.
• Design and implement data architectures, data models, data warehouses, data lakes, and data integration solutions.
• Develop and maintain project plans, delivery schedules, milestones, dependencies, risks, and resource plans.
• Lead data analysis and modeling activities to address business and analytical requirements.
• Guide the selection and application of data technologies, tools, platforms, and delivery approaches.
• Ensure data solutions meet requirements for quality, scalability, maintainability, security, and performance.
• Lead technical discussions with clients, architects, analysts, engineers, and other stakeholders.
• Review technical outputs, data models, integration designs, analytical solutions, and project deliverables.
• Monitor project progress, quality, budget, risks, and delivery timelines.
• Mentor team members and support knowledge sharing, technical development, and consistent engineering practices.
• Promote efficient use of data storage, processing, and cloud resources.
• Apply data security and governance practices throughout data collection, storage, processing, integration, and reporting.
• Protect sensitive business and client data through appropriate access controls, permissions, and secure handling practices.
• Identify and escalate security, privacy, data-quality, and operational risks.
• Communicate data concepts, technical decisions, risks, progress, and recommendations clearly to clients and internal stakeholders.
• Manage multiple projects, priorities, dependencies, delivery schedules, budgets, stakeholder expectations, and team workloads.

What you'll need

• A bachelor’s or master’s degree in Computer Science, Information Systems, Engineering, or a related field; equivalent relevant education and experience may be considered.
• Minimum of 7 years of experience in Data and Analytics projects, including project leadership and delivery management.
• Experience leading project teams and managing project delivery.
• Proven track record of delivering data-driven solutions to clients.
• Strong experience with Python, Apache Spark, SQL, data warehousing, data lakes, big data platforms, data modeling, and data integration.
• Strong experience with data analysis, data transformation, querying, validation, and database development.
• Experience with Oracle, MySQL, and SQL Server.
• Experience designing conceptual, logical, and physical data models.
• Experience designing and implementing data integration solutions.
• Experience with data quality, standards, ownership, metadata, access, and lifecycle controls.
• Knowledge of Tableau and Power BI.
• Familiarity with AWS and Azure data environments.
• Ability to use tools for project planning, delivery schedules, documentation, collaboration, and reporting.
• Ability to write maintainable code for data transformation, validation, automation, and analytics.
• Ability to manage multiple tasks, priorities, dependencies, risks, and deliverables.
• Experience mentoring junior team members and providing technical guidance.
• Ability to apply structured analytical thinking and problem-solving to assess data requirements, resolve data issues, and design practical solutions.
• Ability to adapt to evolving business requirements, data technologies, delivery priorities, project constraints, and client needs.
• Ability to maintain continuous professional development in data engineering, analytics, cloud platforms, data governance, visualization, project delivery, and emerging data technologies.

Nice to have

• Experience with cloud-native data architectures and data engineering services.
• Experience delivering data-driven solutions in complex enterprise environments.
• Experience with data quality automation, metadata management, lineage, and reconciliation.
• Experience with advanced analytics, reporting, or self-service BI solutions.
• Certification in data engineering, analytics, cloud, database, or BI technologies.
• Experience improving data-processing efficiency and optimizing cloud resource usage.
• Experience with additional scripting or programming languages used for data engineering, automation, or analytics.
• Experience developing reusable data-processing frameworks, utilities, or automation components.
• Experience with data migration, reconciliation, metadata management, lineage, and master data practices.
• Experience with database and data-platform performance optimization.
• Experience designing data solutions for high-volume or complex analytical workloads.
• Experience designing or implementing cloud-native data architectures.
• Experience with cloud data warehouses, data lakes, processing platforms, and integration services.
• Experience with cloud monitoring, cost management, resource optimization, and sustainable data-processing practices.
• Experience supporting cloud migration or data-platform modernization.
• Libraries supporting advanced analytics, data quality, profiling, lineage, and workflow automation.
• Reusable data-engineering components and shared analytical frameworks.
• Tools supporting self-service reporting and interactive data exploration.
• Agile delivery methodologies.
• Project portfolio management and governance practices.
• Automated data-quality checks, testing, monitoring, and deployment.
• Experience with source control, CI/CD, workflow orchestration, and data pipeline monitoring.
• Experience establishing data engineering standards and delivery metrics.
• Experience implementing security controls in cloud-based data platforms.
• Experience supporting regulatory, audit, privacy, or compliance requirements.
• Experience with data masking, encryption, role-based access, and secure data integration.
• Experience incorporating security and governance checks into data delivery processes.
• Industry-specific experience is preferred.
• Certifications in data engineering, analytics, cloud platforms, databases, BI, or related technologies are preferred.

Details

• Location: Gurugram.
• Experience with Oracle, MySQL, SQL Server, Tableau, Power BI, AWS, and Azure is required or preferred according to the specific project scope.
• Project deliverables must be completed on time, within budget, and in accordance with agreed standards.
• Data solutions must consider data privacy, retention, classification, lineage, and auditability requirements.
• Candidates may qualify through an equivalent combination of relevant data engineering, data analytics, project leadership, client delivery, technical training, and demonstrated delivery outcomes.