Lead Data Engineer

Position SummaryThe Senior Data Engineer will architect, design, and deliver enterprise-scale data pipelines and cloud-native data platforms using Azure Data Factory and Snowflake. This role is central to powering our analytics, reporting, and AI initiatives by building modern, automated, and scalable data ecosystems. The ideal candidate will combine deep expertise in both ADF and Snowflake with a strong delivery mindset to accelerate data modernization. This position is based in Hyderabad, India.Principal ResponsibilitiesArchitect and build robust, scalable end-to-end data pipelines using Azure Data Factory and design large-scale, high-availability data platforms using Snowflake.Modernize and migrate legacy data warehouses and ETL workloads (e.g., SSIS) into cloud-native solutions leveraging Snowflake and ADF.Design and implement advanced data ingestion, transformation, and curation frameworks for structured and semi-structured data from diverse sources (APIs, streaming, databases).Implement pipeline orchestration, automation, monitoring, and DataOps/CI-CD practices for the entire data lifecycle.Optimize Snowflake schema design, query performance, and storage cost management.Ensure best practices in security, compliance, data governance, and performance tuning across the Azure and Snowflake ecosystem.Collaborate with analytics, BI, and AI teams to deliver timely, trusted, and AI/ML-ready data products.Lead technical design sessions and mentor junior engineers on best practices for ADF, Snowflake, and DevOps automation.Provide production support, including root-cause analysis and performance remediation for data pipelines and platforms.Qualifications & Technical SkillsAdvanced expertise in Azure Data Factory (ADF) for pipeline design, orchestration, and integration.Expert-level experience in Snowflake architecture, including schema design, data sharing, and query performance tuning.Strong proficiency in SQL, data modeling, and performance tuning across both SQL Server/Synapse and Snowflake.Hands-on experience with the broader Azure data ecosystem (e.g., Azure Data Lake, Synapse, Event Hubs).Knowledge of CI/CD practices, Git-based workflow, and DevOps for data pipelines.Proven experience in legacy ETL and data warehouse modernization.Familiarity with Power BI and streaming technologies (e.g., Kafka) is a plus.Demonstrated leadership in building enterprise-scale data platforms.Minimum RequirementsBachelor’s degree in computer science, IT, or a related field.7–10 years of experience in enterprise data engineering/ETL.At least 3 years of hands-on experience with Azure Data Factory.At least 3 years of hands-on, focused experience with Snowflake.Strong knowledge of the Azure cloud ecosystem and modern data architecture principles.About SpinTheoryAt SpinTheory.ai, we are not just building data platforms; we are engineering the future of how organizations harness data and AI. We aim to transform enterprise complexity into clarity, speed, and measurable business value. As a high-growth startup with global ambitions, we thrive on bold thinking, rapid execution, and relentless curiosity.We believe in empowering our people as much as our clients. At SpinTheory, you won't just "do a job"; you will architect the next generation of data and AI ecosystems, working side by side with innovators who challenge the status quo. Flexibility, ownership, and adaptability aren't perks here; they are part of the DNA that fuels our growth. By joining us, you enter a culture where integrity drives action, customer success defines impact, collaboration sparks innovation, and continuous learning is the only constant. Together, we're creating a future where data and AI don't just inform decisions, they accelerate possibilities.Core Values: Integrity, Customer Success, Collaboration, Continuous Learning, and Bold Innovation.