Data Engineer at Weekday AI

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

16 Mar, 26

Salary

0.0

Posted On

16 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Backend Development, Node.js, Data Modeling, ETL/ELT Pipelines, Data Warehousing, Data Quality, Data Governance, APIs, Collaboration, Problem-Solving, Communication, Scalability, Operational Excellence, Product Thinking, Mentoring

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Min Experience: 7 years Location: Bengaluru, Karnataka JobType: full-time As a Senior Data Engineer, you will play a critical role at the intersection of data engineering, product thinking, and operational excellence, building and scaling data systems that directly power product decisions and business outcomes. With a strong foundation in backend development (Node.js) and a product-first mindset, you will design, implement, and operate reliable data pipelines, platforms, and services that enable analytics, experimentation, and data-driven decision-making. This is a full-time role based in Bengaluru, Karnataka, ideal for professionals with 7+ years of experience who enjoy owning systems end-to-end and collaborating closely with product, engineering, and operations teams. Key Responsibilities Design, build, and maintain scalable, high-performance data pipelines and data platforms to support product analytics, reporting, and operational use cases Partner closely with product managers to translate business and product requirements into robust data models, pipelines, and metrics Develop and maintain backend services using Node.js to enable data ingestion, processing, APIs, and integrations Own the full lifecycle of data systems, including development, deployment, monitoring, and ongoing optimization Ensure high data quality, consistency, and reliability through validation, testing, and automated checks Build and optimize data workflows that support real-time and batch processing use cases Collaborate with operations teams to ensure data platforms are reliable, observable, and cost-efficient in production Enable self-service analytics by designing well-documented datasets, schemas, and APIs for internal stakeholders Work with cross-functional engineering teams to integrate data systems with core product and application services Establish best practices for data governance, security, and access control Monitor system performance and proactively identify bottlenecks, risks, and opportunities for improvement Support experimentation, A/B testing, and feature measurement by delivering accurate and timely data Contribute to architectural decisions with a long-term, product-scaled mindset Mentor junior engineers and promote strong engineering and operational standards across the team What Makes You a Great Fit 7+ years of experience in data engineering, backend engineering, or platform engineering roles Strong product orientation, with the ability to think like a Product Manager and align data solutions with user and business needs Hands-on experience with Node.js for building backend services, APIs, or data processing systems Solid understanding of data modeling, ETL/ELT pipelines, and data warehousing concepts Experience working in production environments with a strong focus on operations, reliability, and scalability Ability to collaborate effectively with product managers, engineers, and operations stakeholders Strong problem-solving skills with a pragmatic, outcome-driven approach Experience designing systems that balance speed, accuracy, and maintainability Comfortable owning systems end-to-end, from design through production support Strong communication skills, able to explain complex data concepts to non-technical audiences Experience working in fast-paced, product-driven environments Passion for building data systems that directly impact product decisions and customer experience

Responsibilities

Design, build, and maintain scalable data pipelines and platforms to support analytics and reporting. Collaborate with product managers and engineering teams to ensure data systems meet business needs and maintain high data quality.