Overview

Synechron is seeking a Lead – Data Engineer/Data Analyst to lead Data and Analytics projects and deliver data-driven solutions.

Responsibilities

• Lead and manage Data and Analytics projects from requirements definition through delivery and transition.
• Work closely 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.
• Ensure project deliverables are completed on time, within budget, and in accordance with agreed standards.
• Promote efficient use of data storage, processing, and cloud resources to support sustainable technology practices.
• Python.
• SQL.
• Apache Spark development and data-processing capabilities.
• Ability to write maintainable code for data transformation, validation, automation, and analytics.
• Lead data analysis, modeling, architecture, integration, and solution-design activities while working with clients to understand data needs.
• Manage project delivery through planning, scheduling, progress tracking, risk management, stakeholder coordination, and budget monitoring.
• Lead technical discussions with clients and internal teams and provide guidance on data platforms, models, governance, quality, and integration approaches.
• Mentor team members, review deliverables, ensure quality and timely delivery, and make technical decisions within agreed project standards.

Qualifications

• Certification in data engineering, analytics, cloud, database, or BI technologies.
• Oracle.
• MySQL.
• SQL Server.
• Data warehousing.
• Data lakes.
• Big data platforms.
• Data modeling and data integration.
• Data collection, cleansing, preparation, transformation, and validation.
• Data governance and data quality management.
• Understanding of data structures, relationships, lineage, ownership, access, and lifecycle management.
• Familiarity with cloud-based data solutions.
• AWS.
• Azure.
• Understanding of cloud data storage, processing, integration, scalability, availability, and governance considerations.
• Apache Spark.
• Frameworks and libraries used for Python-based data engineering and analytics.
• Components supporting data ingestion, transformation, validation, integration, and analytics.
• Tools supporting data visualization and business intelligence, including Tableau and Power BI.
• 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.
• Data and Analytics project delivery.
• Project planning and delivery scheduling.
• Data architecture and modeling.
• Data integration and pipeline development.
• Data governance and quality practices.
• Client and stakeholder collaboration.
• Technical reviews and delivery reporting.
• Team leadership, mentoring, and project coordination.