Data Engineer - (Remote, Spain) at Bark

Madrid, Community of Madrid, Spain -

Full Time

Start Date

Immediate

Expiry Date

13 May, 26

Salary

0.0

Posted On

12 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Pipelines, Event Tracking, Streaming Layer, Data Warehouse, Real-time, Scalability, Reliability, Data Validation, Data Modelling, Python, AWS, Kinesis, Kafka, Schema Registries, CI/CD, SQL

Industry

technology;Information and Internet

Description

About Bark Bark is an online services marketplace connecting customers with professionals across over 1,000 categories. Operating in nine countries including the UK, US, Australia, Canada, and New Zealand, we're transforming how people find trusted service providers for everything from home improvement to professional services. Our platform uses cutting-edge technology to match customers with the right professionals quickly and efficiently. With a global team of over 220 people, we're currently undergoing an exciting transformation: migrating from a lead generation model to a full marketplace platform with subscription-based pricing. As a profitable, PE backed scale up (EMK Capital), Bark offers the best of both worlds: the agility and innovation of a fast moving business combined with financial stability and resources for growth. We recently launched our new marketplace model in Australia (Q4 2025) and are preparing for rollout to the UK and US markets in 2026. You'll have genuine ownership, responsibility, and the opportunity to shape our commercial strategy during a pivotal transformation phase with the chance to make your own contribution to our journey. About the Role We are looking for a Data Engineer to join our staff data engineer and form a new squad. This role is for an engineer with experience in data pipelines for event tracking in the streaming layer. You will work on our data streaming platform which captures events from different clients into our Data Warehouse. You will own the full data lifecycle for real-time event tracking, ensuring scalability, reliability, and cost-effectiveness. While basic components are built, a large rollout of event tracking across different teams is required, presenting significant data validation, data modelling and scaling challenges ahead. You will work closely with analysts, engineers and product managers to enable accurate reporting in new product features and business KPIs. These events also fuel our AI feature stores and models. Our data stack is written in Python and hosted in AWS. You will support frontend and backend engineers to instrument event tracking so those can be collected across the product domains. Responsibilities Build and operate a scalable data platform ingesting real-time events with a high-throughput rate. Collaborate with analysts, engineers and product managers to understand user needs and take ownership of producing new event tracking functionality. Implement automations, high data quality controls, ensure data integrity in the ingested data, and create necessary monitoring alerts. Improve existing data pipelines architecture and workflows in collaboration with stakeholders. Required Skills and Experience Hands-on experience in a cloud data platform for event streaming such as Kinesis, Pub-Sub or Kafka. Experience deploying and maintaining Python services in a major cloud environment (AWS, GCP, Azure). Specific experience with the AWS stack, including Kinesis, Lambdas, Glue, Firehose, and Athena, is highly desirable. Great skills improving and operating Schema Registries and Data Catalogs (Glue, Databricks, etc.) Relevant CI/CD experience (e.g., GitHub Actions, Gitlab Pipelines) automating tests and updates in schema registries and lambda releases. Solid experience with SQL and data warehousing, data lake environments (e.g. DataBricks, BigQuery, Redshift, S3). Knowledge and practical experience with data modelling, proto or AVRO schemas, and managing schema evolution. Familiarity with cloud observability tools (e.g. Datadog, NewRelic, or Cloudwatch). Desired skills and experience Production experience with containerization (Docker), orchestration (Kubernetes, AWS ECS/Fargate, etc.) and IaC (Terraform, Crossplane) Large scale data processing with PySpark and Flink Datamart creation with DBT Airflow job orchestration Interview Process Screening Call with Talent Partner (30 mins) 1st Stage - Hiring Manager Stage (30 mins) 2nd Stage - Technical Interview (45/60 mins) 3rd Stage - Values interview (30 mins) Diversity Statement At Bark, we are a platform for people, revolutionising the way professionals and individuals connect since 2014. Our culture is defined by excitement, ambition, and a commitment to raising the bar. We value diversity, equity, inclusion, and belonging (DEIB) and are dedicated to embedding these principles into everything we do. We are committed to fostering an inclusive environment where everyone can thrive, and our focus is on hiring, retaining and developing a globally diverse workforce that is passionate about excelling our platform and supporting our customers succeed. Be part of our dynamic team, where bold ideas thrive, and create a future worth shouting about.

Responsibilities

The role involves building and operating a scalable data platform for ingesting high-throughput, real-time events, while collaborating with stakeholders to implement new event tracking functionality and ensure high data quality.