Lead Data Engineer / Data Analyst - Python, Spark, SQL & Cloud

About the role

Synechron is looking for a Lead Data Engineer / Data Analyst to lead Data and Analytics projects and deliver data-driven solutions. The role combines technical expertise in data engineering, analytics, data architecture, modeling, integration, visualization and governance with project delivery and team leadership. You will work closely with clients and internal teams to understand business requirements, design data solutions, manage delivery plans and ensure projects finish on time, within budget and to agreed quality standards.

Key responsibilities

• Lead and manage Data and Analytics projects from requirements definition through delivery and transition.
• Work with clients and internal stakeholders to understand business needs and build data-driven solutions.
• Provide technical guidance to junior team members and project teams.
• Oversee data collection, cleansing, transformation, validation and preparation.
• Design and implement data architectures, data models, data warehouses, data lakes and integration solutions.
• Develop project plans, schedules, milestones, dependencies, risks and resource plans.
• Lead data analysis and modeling, guide technology choices and review technical outputs and deliverables.
• Mentor team members, monitor progress, quality, budget and timelines, and promote efficient use of data and cloud resources.

Required profile

• Strong experience in data engineering, analytics, automation or data processing with Python.
• Strong SQL experience covering analysis, transformation, querying, validation and database development.
• Experience with Apache Spark, Oracle, MySQL and SQL Server, and data warehousing and data lakes.
• Knowledge of Tableau and Power BI; familiarity with AWS and Azure data environments.
• Preferred: cloud-native architectures, data quality automation, metadata management, lineage and certification in data engineering, analytics, cloud, database or BI.

Required skills

• Python, SQL, Apache Spark, Oracle, MySQL, SQL Server
• Data warehousing, data lakes, data modeling and integration
• Tableau, Power BI, AWS, Azure
• Project planning, delivery scheduling, documentation and reporting