Job Information

- Date Opened 27/04/2026
- Job Type Full time
- Industry IT Services
- Work Experience 3 - 6 years
- Salary As per the company norms
- City Noida
- Province Uttar Pradesh
- Country India
- Postal Code 201301

About Us

At ScaleupAlly, we believe that technology improves all aspects of lives. That is why we are geared towards becoming a tech ally of great ideas. The aim is to be the remote in-house tech team of these ideas. We work with Start-ups, Founders, and Leaders around the globe with ideas of Web and App Development, Business Intelligence and Data Visualization. We achieve our aim by building the long-lasting dynamic teams made of the top talent across the globe managed by experienced in-house Technical Leads. At ScaleupAlly, we build, manage and care our distributed teams like no one else. It’s a whole new approach to make you rethink what your idea is capable of.

Job Description

Data Engineering & Architecture

-
Design, develop, and maintain scalable, high-performance data pipelines

-
Work extensively with Azure Data Factory and Microsoft Fabric

-
Build robust ETL/ELT frameworks using Python

-
Design and optimize Lakehouse / Data Warehouse architectures

-
Handle large-scale datasets efficiently (high volume and throughput)

-
Write and optimize complex SQL queries for performance and reliability

-
Integrate data from multiple sources including APIs, transactional systems, and external platforms

Leadership & Delivery (Hands-on)

-
Lead and mentor a team of data engineers while remaining actively involved in coding and solution design

-
Perform hands-on development for critical pipelines, complex transformations,



and performance optimisation.

-
Conduct code reviews and enforce best practices, design patterns, and coding standards

-
Act as the technical owner for data engineering deliverables

Quality, Performance & Reliability

-
Implement data quality checks, validations, and monitoring

-
Optimize pipelines for performance, scalability, and cost

-
Ensure reliability, fault tolerance, and error handling in production systems

-
Follow data security, access control, and compliance best practices

-
Lead troubleshooting, root-cause analysis, and production issue resolution

Collaboration & Continuous Improvement

-
Work closely with BI, analytics, product, and business teams

-
Translate business requirements into scalable technical solutions

-
Stay up to date with modern data engineering tools, technologies, and techniques

-
Proactively suggest architectural and process improvement

Requirements

- 3-6 years of experience in the Data Engineering field.

-
Solid hands-on experience in Python for data engineering, including building and maintaining production-grade, large-scale data pipelines

-
Advanced experience with Azure Data Factory and Azure-based data platforms for orchestration, integration, and scalable data processing

-




Working experience with Microsoft Fabric, including Lakehouse and data engineering workloads, along with a strong understanding of ETL/ELT and data warehousing concepts

-
Expert-level SQL skills covering complex query development, optimization, indexing, and partitioning for high-performance systems

-
Proven experience handling large-volume, high-throughput data and distributed processing setting.

-
Experience with analytics and visualization platforms such as Power BI

-
Knowledge of Delta Lake, Spark, and distributed data processing frameworks

-
Experience implementing CI/CD practices for data pipelines and data engineering workflows

-
Exposure to data governance, lineage, metadata management, and compliance-driven environments such as fintech or high-transaction systems

-
Hands-on leadership mindset with strong ownership and accountability for outcomes

-
Ability to mentor, guide, and grow junior engineers while leading by example

-
Clear and effective communication with technical and non-technical stakeholders

-
Strong problem-solving, analytical reasoning, and decision-making skills

Benefits

- 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

📌 Data Engineer (India)
🏢 Scaleupally
📍 India