BIG DATA ENGINEER

Role: Associate Principal Engineer- BIG-DATA-ENGINEER

Experience: 10 - 15 Years

Location: Sandy Springs, Atlanta(3 days in a week)

Rounds of interviews: 2 internal + 1 client round

Must have skills :

Data Engineering and Integration Expertise, Data Governance and Security Knowledge, Databricks, Technical delivery

Good to have skills:

Data Modeling (Capable)

Job Description :

• Oversee the delivery of data projects, including data pipelines, warehouses, lakes, and analytics platforms.
• Collaborate with architects, data engineers, and data scientists to deliver robust and scalable data solutions.
• Provide hands-on guidance on data modeling, ETL/ELT workflows, and cloud-based data architectures.
• Develop and execute detailed project plans, ensuring timely delivery within scope and budget.
• Manage competing priorities across multiple data delivery streams.
• Drive adherence to Agile or hybrid project management methodologies.
• Stakeholder Engagement Serve as the primary technical liaison between clients and delivery teams for all data-related initiatives.
• Understand client requirements, translating business goals into actionable data solutions.
• Conduct regular status updates and stakeholder reviews to ensure alignment and satisfaction.
• Team Coordination Lead onshore and offshore teams to deliver high-quality data solutions.
• Foster a collaborative work environment, ensuring effective communication and teamwork.
• Identify and address skill gaps within the team through mentorship or training.
• Data Quality and Governance Implement data governance policies, ensuring compliance with standards and regulations.
• Oversee data quality initiatives, including validation, monitoring, and issue resolution.
• Promote the adoption of best practices for data security, integrity, and privacy. Risk and Issue Management Identify delivery risks and develop mitigation strategies.
• Address technical and operational challenges proactively, escalating issues when necessary.
• Reporting and Metrics Track and report on delivery metrics, including data accuracy, timeliness, and system performance.
• Provide regular updates to leadership on project health, risks, and financials.