Job Title: Data Engineer
Business Unit:
ScaleupAlly
Company:
Admito Technologies Pvt Ltd.
Location:
Noida
Type:
Full Time
About the Company:
ScaleupAlly is powering the world's startups and leaders. We provide on-demand access to the experts in technology solutions development. ScaleupAlly Talent Network is a group of highly skilled engineering leads, developers, designers, and quality analysts from around the world who are changing the rules of the workforce. The mission is to expand the technological capabilities of Startups and Leaders by building a managed and remote agile team.
Purpose of Job:
SacleupAlly is looking for a Hands-onLead Data Engineer who will lead the data engineering team while actively contributing to project development. This role requires strong technical expertise in Python, Microsoft Fabric, Azure Data Factory, SQL Databases, and large-scale data pipelines, along with the ability to set engineering standards, follow best practices, and deliver production-grade solutions.
The ideal candidate will work on high-volume data systems, take ownership of architecture and implementation, and mentor team members without moving away from hands-on development.
Essential Qualifications:
- Bachelor's degree in any discipline.
- Information Systems, or a related field.
- Holds at least 3-6 years of demonstrable experience in data engineering.
Skills:
ADF l Microoft Fabrics l SOL l ETL/ELT l Power BI l Python l
Duties:
- Lead and mentor a team of data engineers while remaining hands-on with critical development, solution design, and technical decision-making.
- Own end-to-end data engineering deliverables, including architecture, development, optimization, and production support.
- Design, build, and maintain scalable, high-performance data pipelines and ETL/ELT frameworks using Python, SQL, Azure Data Factory, and Microsoft Fabric.
- Architect and optimize Lakehouse and Data Warehouse solutions to efficiently handle large-scale, high-volume data workloads.
- Ensure data quality, reliability, security, and compliance through robust validations, monitoring, fault tolerance, and access controls.
- Perform code reviews, enforce engineering best practices, and drive performance, scalability, and cost optimization initiatives.
- Integrate data from APIs, transactional systems, and external platforms.
- Lead troubleshooting, root-cause analysis, and resolution of complex production issues.
- Collaborate closely with BI, analytics, product, and business stakeholders to translate requirements into scalable technical solutions.
- Evaluate emerging tools, modern technologies, and architectural patterns, proactively driving process and platform improvements.
Required Qualifications:
- Strong hands-on expertise in Python and SQL for building and optimizing production-grade data pipelines.
- Solid understanding of ETL/ELT, Lakehouse, and data warehousing architectures.
- Advanced experience with Azure Data Factory and Microsoft Fabric for scalable data engineering workloads.
- Proven ability to handle high-volume, high-throughput data systems with focus on performance and reliability.
- Experience with distributed data processing (e.g., Delta Lake, Spark) and CI/CD for data pipelines.
- Exposure to data governance, lineage, metadata management, and security best practices.
- Hands-on leadership with strong ownership, mentorship, and engineering standards.
- Excellent communication, problem-solving, and stakeholder management skills.
Benefits and Additional Information:
- Working hours: 10:00 AM – 7:00 PM.
- Working days: 5 days a week (plus 1st & 3rd Saturdays working)
- Medical Insurance coverage for employees.
- Provident Fund (PF) facility.
- Quarterly parties and yearly outings/trips for team bonding.
- Regular check-ins with leadership for growth and feedback.
- Recognition awards to celebrate high performance.
- Fun activities and team engagement sessions throughout the year.
Pay: ₹900,000.00 - ₹1,200,000.00 per year
Benefits:
- Health insurance
- Leave encashment
- Life insurance
- Paid sick time
- Paid time off
- Provident Fund
- Work from home
Work Location: In person
