Lead Data Engineer at - · Remote only · 8 - 13 years · ₹10L - ₹33L / yr · Remote only · Posted 23 Dec 2025

Role: Lead Data Engineer Core
Responsibilities: Lead end-to-end design, development, and delivery of complex cloud-based data pipelines.
Collaborate with architects and stakeholders to translate business requirements into technical data solutions.
Ensure scalability, reliability, and performance of data systems across environments. Provide mentorship and technical leadership to data engineering teams. Define and enforce best practices for data modeling, transformation, and governance.
Optimize data ingestion and transformation frameworks for efficiency and cost management. Contribute to data architecture design and review sessions across projects.
Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
8+ years of experience in data engineering with proven leadership in designing cloud native data systems.
Strong expertise in Python, SQL, Apache Spark, and at least one cloud platform (Azure, AWS, or GCP). Experience with Big Data, DataLake, DeltaLake, and Lakehouse architectures Proficient in one or more database technologies (e.g. PostgreSQL, Redshift, Snowflake, and NoSQL databases).
Ability to recommend and implement scalable data pipelines Preferred Qualifications: Cloud certification (AWS, Azure, or GCP). Experience with Databricks, Snowflake, or Terraform. Familiarity with data governance, lineage, and observability tools. Strong collaboration skills and ability to influence data-driven decisions across teams.

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· Lead the end-to-end design and development of scalable, high-performance data pipelines and ETL/ELT frameworks aligned with modern data engineering best practices.
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· Partner with analysts, data scientists, and business leaders to define and deliver reliable data models, quality frameworks, and SLAs that power key business insights.
· Ensure optimal pipeline performance and throughput, with clearly defined SLAs and proactive alerting for data delivery or quality issues.
· Collaborate with platform, DevOps, and architecture teams to build secure, reusable, and CI/CD-enabled data workflows that align with enterprise architecture standards.
· Establish and enforce the best practices in source control, code reviews, testing automation, and continuous delivery for all data engineering components.
· Lead root cause analysis (RCA) and preventive maintenance for critical data failures, ensuring minimal business impact and continuous service improvement.
· Guide the team in establishing standards for data modeling, transformation logic, and governance, ensuring long-term maintainability and scalability.
· Design and execute comprehensive testing strategies—unit, integration, and system testing—ensuring high data reliability and pipeline resilience.
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· Create and maintain detailed technical documentation, including data architecture diagrams, process flows, and integration specifications for internal and external stakeholders.
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Qualifications
· 7 to 10 years of hands-on experience in data engineering roles with a proven record of building scalable and secure data platforms.
· Over 5 years of experience in scripting languages such as Python for data processing, automation, and ETL development.
· 4+ years of experience with Snowflake, including performance tuning, security model design, and advanced SQL development.
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· 5+ years of experience in writing complex, highly optimized SQL queries on large datasets.
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· Experience with CI/CD pipelines, automated testing, and code versioning tools (e.g., Git).
· Familiarity with dbt or similar transformation tools and best practices for modular transformation development.
· Exposure to data visualization tools like Power BI for supporting downstream analytics is a plus.
· Strong interpersonal and communication skills with the ability to lead discussions with technical and business stakeholders.
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Bachelor’s or Master’s degree in Computer Science/Information technology or related field.
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The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Responsibilities and JD
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About Us:
The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
Job Summary:
We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.
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Application Details
Ready to make an impact? Apply today and become part of the QX Impact team!
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