Data Engineer

The Data Engineering team’s mission is to ensure high-quality data to enable data-informed decision-making across Asana. You will build data artifacts that are leveraged by a wide range of stakeholders in the marketing domain, and create frameworks and tooling used by all data and analytics engineering teams. In this role, you will also partner both with business stakeholders and with the Data Infrastructure team. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve Design, implement and scale end-to-end data products that support growing data processing and analytical needs. Influence best practices in Databricks and cloud-based data engineering, driving innovation and adoption across teams. Leverage AI to build self-serve tools and accelerate Data/GTM workflows. Establish trust and strong relationships across business and technical teams, ensuring alignment on data strategy and execution. Implement systems that guarantee data quality, governance, and availability. About you 3+ years of hands-on experience in Data Engineering or Software Engineering. Degree in computer science, engineering or equivalent technical field experience. Proficient in cloud-based data processing and storage technologies like Databricks, Spark, Airflow. Fluent in SQL and proficient in at least one modern programming language (e.g., Python, Scala, Java). Proactive self-starter with a proven ability to identify opportunities, propose innovative solutions, and execute them effectively. Excellent communication skills, with the ability to clearly articulate complex technical concepts to non-technical stakeholders. Demonst

WHAT IS BOX? Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift. WHY BOX NEEDS YOU Data Engineering initiative inside box is expanding and this role will help build the data platform engineering features and capabilities of the cloud cost management platform. In this role you will be working alongside our team building data pipelines, support our product and analytics team members, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. WHAT YOU'LL DO Work with a team of high-performing data engineers and analysts to identify business opportunities, design and build scalable data solutions Build and own data pipelines that clean, transform, and aggregate data from disparate sources Create and maintain optimal data pip

A Career with Point72’s Market Intelligence Team On our proprietary research team—Market Intelligence—you’ll partner with our Investment Professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques to alternative data sets. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our industry researchers, product managers, and data scientists and engineers work together to build compliant research products. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. What you'll do Data Engineers on the Proprietary Research team design and build solutions that enable investment professionals to effortlessly, extract insights from large, complex compliance approved structured and unstructured data sets. As a member of our Data Engineering team, you will work closely with investment professionals, researchers, and data scientists to design, build, and launch robust end-to-end data pipelines and tools that that help extract the most value out of Point72’s data assets. In this role, you will: Develop and support big data processing pipelines including but not limited to ingestion, transformation, and end-customer delivery Build out cloud-based infrastructure using distributed techniques for other data engineers / data scientists / researchers Be at the forefront of new technology developments with respect to the handling and processing of big data and conduct proof of concepts evaluations of new technologies Build and support visualization and exploration capabilities around our big data sets. What's required Experience or demonstrated interest in big data technologies 3+ years of experience in Data Engineering or related field Strong experience in Python Development Experience with Spark or Scala Ability to

A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Design and build scalable, high-performance backend systems that power investment services and AI-driven applications, and own their end-to-end lifecycle Build and operate robust data pipelines for batch and streaming workloads to ingest, transform, validate, and deliver data to models and downstream consumers Integrate and productionize generative AI capabilities and large language model solutions, including model serving, embeddings, and API-based workflows to augment investment workflows Implement and maintain microservices and APIs that expose data and model functionality with a focus on reliability, low latency, and security Optimize system performance and resilience through monitoring, observability, capacity planning, and automated incident response Lead cross-functional delivery of prototypes into production by collaborating with data scientists, researchers, product owners, and operations teams Build and maintain CI/CD pipelines, automated testing, and deployment practices to accelerate safe delivery and rollback of services Mentor and coach engineers on backend and data engineering best practices, help grow engineering capability, and contribute to the technical roadmap Collaborate with security, compliance, and infrastructure partners to ensure data governance, access controls, and operational controls are integrated into solutions WHAT'S REQUIRED Bachelor's degree in computer science, software engineering, or a related technical field At least 5 years of professional software enginee

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. This is a full-time position offered exclusively on a Contract of Employment (Umowa o Pracę) . Please note that this is a hybrid role , requiring employees to work from our Warsaw office (Centrum Koneser) at least 3 days per week . We are not considering fully remote or B2B arrangements for this position. About Open Intelligence : We are the Activation arm of WPP Open Intelligence. Our team builds the foundational data infrastructure and high-performance edge services that power WPP’s position in the market. With approximately one-third of all global media spend flowing through WPP, our platform operates at the core of this massive network—deeply integrated and adopted by the largest supply-side partners in the AdTech industry. Operating at our scale presents unique engineering challenges. Our edge services currently handle over 60,000 classification requests per second, while our contextual classification pipelines process 10,000 requests per second. With operations spanning the US, UK, and ongoing expansion into EMEA and APAC, our infrastructure continuously interacts with up to 98% of the po

The Data Science & Analytics team at Asana is how the company turns data into decisions — defining the questions that matter, surfacing the answers, and making sure insight is at the center of every critical product and business call. As a Senior Analytical Engineer, you sit at the intersection of Data Engineering, Analytics, and Data Science, and you own the data foundations for a business domain end to end. Your mandate is to turn raw data into reliable, business-ready datasets that PMs, analysts, data scientists, and leaders actually trust and use — and to define the business logic and metric standards that make AI-powered self-serve trustworthy. You consume governed Silver tables and produce the Gold layer and semantic layer beneath Asana's most important metrics, dashboards, and Genie spaces. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday, with the option to work from home on Wednesdays and, depending on the work and the teams you partner with, on Fridays. If you're interviewing for this role, your recruiter will share more about the in-office expectations. What you'll achieve: Own the Gold layer for a given business domain (e.g. PLG funnel, marketing attribution, revenue, NPI/AWM): Design and continuously improve the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on. Implement the canonical business logic behind your domain's core KPIs: Translate KPIs into governed, versioned metric marts that resolve "this number doesn't match" disputes for good. Build and curate the semantic layer and Genie spaces that power self-serve in your domain: Author the metadata, documentation, and prompt/metric definitions that let stakeholders query governed data in plain language through Claude and Databricks Genie. Own the metric dictionary for your domain: a single source of truth for what each metric means, who owns it, a