Principal Data Engineer

Role Overview: As a Principal Software Engineer - Data, your role will be to act as a hands-on technical leader and a key communicator with stakeholders as part of the Data Products team. You will directly contribute to designing and developing enterprise-grade data systems while serving as a bridge between engineering teams and business partners. Key Responsibilities: - Drive development efforts by contributing high-quality, scalable, and maintainable code across data pipelines, APIs, and platform components. - Own the communication of project deliverables, timelines, and risks to internal and external stakeholders to ensure alignment at every step. - Understand customer needs and translate them into technical solutions, partnering closely with product, analytics, and engineering teams. - Design and deliver robust and future-proof data architectures supporting analytics, APIs, and machine learning initiatives. - Lead the technical execution of key projects, ensuring clear communication of progress and proactive resolution of roadblocks. - Co-develop architectural roadmaps, implementation plans, and go-live strategies cross-functionally to meet business requirements. - Participate in stakeholder reviews and provide updates on technical progress, dependencies, and constraints. - Guide platform-level optimization, including cost efficiency, performance, reliability, and maintainability. - Set best practices for data governance, lineage, quality, and security in a distributed data environment. - Mentor engineers to foster a strong technical culture and continuous learning environment. Qualifications Required: - 8-12 years of development experience in data engineering, with direct contribution to 24x7 production systems. - Advanced skills in Python and/or Golang, SQL, and current cloud data platforms such as Databricks, BigQuery, Snowflake, etc. - Strong experience in communicating complex project plans and deliverables to both technical and business audiences. - Experience in developing and operating scalable data pipelines, APIs, and data platform components in real-world environments. - Deep understanding of batch and real-time data architectures, data modeling, and data warehousing. - Hands-on experience with cloud-native ecosystems like GCP, AWS, or Azure, CI/CD pipelines, and infrastructure as code. - Proficiency in setting up data observability, quality frameworks, and governance controls in distributed systems. - Demonstrated success in stakeholder engagement, influencing outcomes, and building long-term trust. - Technical leadership in prior roles with clear contributions to architecture, development, and delivery. - Mentoring experience and a passion for helping others grow technically and professionally.,