India Engineering Lead (Data)

Salary

₹80 - 100 LPA

Min Experience

8 years

Location

Bangalore

JobType

full-time

About the role

Overview

Company name: Saltmine | HQ Location: San Francisco, California | Website | LinkedIn

 

Role:  India Engineering Lead (Data)

  • Salary: Rs. 80-100 lakhs per annum
  • Experience: 8-10 years
  • Location: Bangalore (Hybrid)
  • Type: Full-time

 

Responsibilities

  1. Establishing and leading the Data Team:
  • Build and lead a lean world-class data team from scratch(0-1), comprising data engineers, analysts, and scientists.
  • Provide mentorship, guidance, and technical leadership to team members, fostering a culture of continuous learning and innovation.
  • Develop and implement effective strategies for talent acquisition, onboarding, and retention.
  1. Building Application Layer Data Products:
  • Design and develop robust, scalable data products to address business needs, with a focus on the application layer.
  • Collaborate closely with cross-functional teams to understand requirements and translate them into actionable technical solutions.
  • Drive the end-to-end development process, from ideation and prototyping to deployment and maintenance.
  1. Data Engineering:
  • Oversee the design, implementation, and optimization of Saltmine's data architecture and infrastructure.
  • Lead efforts to address data discrepancy issues and real-time data access challenges, ensuring data integrity and availability.
  • Architect and build data pipelines for efficient data ingestion, processing, and storage.
  1. Data Analysis:
  • Define and implement best practices for data analysis and reporting, enabling stakeholders to derive actionable insights from Saltmine's vast data repository.
  • Partner with business teams to identify key performance metrics and develop interactive dashboards and visualizations for real-time monitoring and decision-making.
  1. Data Governance and Security:
  • Define and enforce data governance policies and procedures to ensure compliance with regulatory requirements and industry standards.
  • Implement robust security measures to protect Saltmine's data assets against unauthorized access, breaches, and vulnerabilities.
  • Establish monitoring and auditing mechanisms to track data usage, access patterns, and security incidents.



Qualifications:

  1. Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field.
  2. Proven 8-10 years of experience in data engineering, with a focus on optimizing and troubleshooting complex data systems.
  3. Strong proficiency in programming languages such as Python, SQL, and Java/Golang/JavaScript, with hands-on experience in software development and data engineering.
  4. Expertise in data modeling, ETL processes, and database technologies (e.g., SQL, NoSQL, Hadoop, Spark).
  5. Experience with data visualization tools and BI platforms (e.g., Sisence, Tableau, Power BI).
  6. Solid understanding of statistical analysis, machine learning techniques, and data science methodologies.
  7. Excellent communication skills, with the ability to effectively collaborate with stakeholders at all levels of the organization.
  8. Demonstrated leadership qualities, including strategic thinking, decision-making, and team-building abilities.

About the company

About us

Saltmine is a rapidly growing technology firm in the Commercial Real Estate space disrupting the $300B workspace design-build market. We are applying modern technology to transform the process by which office design is done from workplace strategy to programming to design and procurement. With deep roots in technology and architecture design, we've built a first of its kind SaaS platform that empowers occupiers and their business partners to design inspiring and efficient spaces. The company is headquartered in San Francisco with offices in NYC, Boston, Budapest, Vietnam, and Singapore, with an incredibly talented group of employees. We have closed our Series A funding round from marquee VC firms from Singapore & USA.

 

Skills

Data Engineering