Manage both people and data for lasting impact in our culture and clients' goals...
Thinking Machines is a technology consultancy building AI & data platforms to solve high impact problems for our clients. Our vision is for the Philippines to become a global hub for data science. To do that, we create data cultures, one organization at a time.
We’re a company made up of intellectually curious, civic-minded, forever-learning individuals. We believe that great data science products are built with care for people, and that the best way to drive inclusive innovation is to start with a diverse team.
Our field of work is incredibly dynamic, so we want to work with people who are committed to growing with us. We want to hire people who can demonstrate an ability to learn, then provide them with personalized coaching, growth opportunities, and a great working environment to get them to world-class.
The Data Engineer Manager is responsible for the outcomes of one team of roughly 3 to 5 people. They will manage this team of data engineers across multiple client and internal projects. They are responsible for their team’s overall competence and execution on projects, and guiding that competence via training, staffing, and program design.
The engineering manager is expected to write code. They can be the tech lead for a small project, but will not be expected to tech lead more than one project or any large client project (>3 people). They may be tapped for advice as a senior engineer by the various project teams.
They serve as the technically savvy voice that asks business and product questions of the engineers on their teams, ensuring that the code we are writing matches the product and business needs and can scale appropriately as those needs grow. They use their technical expertise to envision and build systems rooted in company strategy. They are accountable for the Objectives and Key Results of their team.
What are you expected to do in this job?
Ensure team success
Be a fantastic un-blocker
Provide professional guidance to the Individual Contributors who report to you
Help ICs understand how their work contributes to team goals
Expand the ICs’ skill sets and guide their career growth
Hold regular one-on-ones, code review sessions, feedback sessions, and performance evaluations
Coach web engineers in technology impact via code review, architecture review, and in professional impact (i.e. soft skills and process improvements)
Design, implement, and maintain people management processes (e.g. training curriculums, on-call systems, hiring and retention)
Work with other tech leads and management to build great technology that solves hard problems
Consistently make culture choices that positively impact all of engineering
Effectively work with senior leadership in setting the strategic direction for their team
Able to communicate and coordinate with multiple teams and operate well in ambiguity
Experience in architecture design for a deployed large-scale service
Experience in leading successful technology projects as a technical leader, working well with other business units and stakeholders
Competence in handling complex stakeholder interactions (e.g. complex scoping, managing trade-offs, designing and running tech programs that cut across multiple teams)
Minimum 3 years of experience in software engineering
Data engineers collect and consolidate data from various sources, secure them and transform them into useful forms so that the rest of the team can work data science magic on them.
Data Engineers are responsible for building systems for collecting, transforming, and storing data. This can range from writing a short script that periodically calls an API to creating a website scraper to architecting and building a complete data collection and data warehousing system.
On a normal day, data engineers might be architecting an analytics platform for a SaaS company or debugging a data ETL pipeline that pipes 1TB of data per day.
Our data engineers work with the machine learning team to create feature libraries, model training and deployment workflows, and
Our usual stack consists of Airflow, Streamsets, or Dagster in a GCP or AWS environment
We offer the following compensation and benefits:
Competitive salary — the compensation amount is positively correlated with the difficulty and scope of the job, relevant experience, fit, and skill factors.
Fully remote — due to the global pandemic, we have shifted to a fully remote company for the foreseeable future while we monitor the situation.
Individual professional development budget — an annual budget for conferences, training courses, books, and software are available to sharpen your skills and build new ones to help you grow in your role.
Full health benefits — generous health insurance package.
Regular 1:1 meetings with the leadership team to discuss career and personal goals, job progress and any questions and concerns.