Data Engineering Director

Remote - Gurugram, Haryana, India

Applications have closed

IMMO

The new way to invest in residential real estate at scale.

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We are IMMO, a real estate fintech disrupting residential real estate. IMMO makes buying, selling and renting an easy, hassle-free experience. We are building Europe's largest residential fintech platform for institutional investors to enable programmatic real estate investment at scale, unlocking the residential asset class. For sellers, we provide a quick and transparent sales process with a guaranteed offer in 48 hours and our renters enjoy high quality and newly refurbished properties with excellent service.

Founded in 2017, we’re a fast-growing start-up and have received significant institutional and venture funding backed by top European and Global VCs. The team includes serial entrepreneurs and industry leaders with experience from McKinsey, Goldman Sachs, Blackstone, Uber, Amazon, Procter & Gamble, BlackRock, Morgan Stanley, Google, WeWork, etc. and we are looking for talented people to join us on our mission.

We put data at the heart of decision making and believe that opinions don’t affect facts, but facts affect opinions. We are straightforward, open-minded, creative and not afraid to challenge others. If this sounds like you too… read on!


You Will:

  • Develop the BI & Data Science function together with the Head of BI & Data Science and other analytics leaders. Support the successful adoption of analytics across Immo with easy and quick access to relevant data.
  • Work closely with our analytics and engineering teams and help them to work with data more effectively and efficiently. Understand data problems and needs. Propose and deliver appropriate solutions.
  • Create the roadmap for and establish our central data platform capabilities. Build and lead a team of data engineers. Agree and drive the implementation of a common data architecture with our product and engineering teams.
  • Lead efforts to resolve ad-hoc challenges across the business. Identify opportunities on how to use data, insights and analytics more powerfully to automate and optimise our processes and solutions.

Requirements

You Have:

  • You have previous experience leading data engineers or analytics teams successfully solving data engineering and architecture challenges in a complex and fast-moving business environment.
  • A good understanding of the different data needs of analytics and engineering teams and how they could be met. Ideally, you have already successfully supported analytics and/or engineering teams with data platform capabilities. You effectively enabled & trained others to work with the tools and services you provided.
  • You have strong experience working with SQL and RDBMS. Ideally, you already worked with or even managed cloud data warehouses like Snowflake or BigQuery. You used or ideally managed message brokers (like Kafka) to share data updates across services and applications.
  • You have a solid understanding of software design principles, DevOps and cloud infrastructure. MLOps, big data or real-time processing is a plus.
  • You’re a self-starter who is comfortable working autonomously and with teams located across our offices. You’re not afraid to get your hands dirty, prioritise your focus based on impact, and are able to own a project from start to finish

Benefits

  • Flexible leave policy
  • Flexible working policy, we believe that work is something you do not when you have to do it
  • Mental Health Assistance
  • A truly collaborative culture where the best ideas win, not the person with the most senior title
  • The ability to figure out your own solutions, and the responsibility to implement them
  • A culture that is devoid of egos, where People > Product > Profits

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Big Data BigQuery DevOps Engineering FinTech Kafka MLOps RDBMS Snowflake SQL

Perks/benefits: Flex hours Health care Startup environment

Regions: Remote/Anywhere Asia/Pacific
Country: India
Job stats:  6  3  0

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