Senior Data Engineer, Platform Data

This is a fully remote position, open to applicants in Germany.

📋 Description

• Design, construct, and manage production data pipelines that drive Leadfeeder's product functionalities — encompassing ingestion, enrichment, processing, and serving.

• Develop and sustain streaming and real-time ingestion systems that efficiently transfer event data across the platform at scale and with minimal latency.

• Take ownership of the cloud infrastructure that supports the pipelines — including compute, storage, networking, security, and observability — all designed and managed through code.

• Collaborate with product and ML engineers to provide datasets and pipelines that enable product-facing features and AI/ML workflows.

• Establish data quality, observability, and reliability measures across the pipelines to ensure early detection of issues, minimized incidents, and trustworthy data for downstream teams.

• Promote engineering best practices within the team: code review, testing, CI/CD for data, infrastructure-as-code, performance optimization, and cost management.

• Work alongside engineering, product, and ML teams to convert product requirements into scalable, thoroughly documented data systems.

⛳️ Requirements

• Over 10 years of hands-on experience in data and/or software engineering, playing a key role in production data pipelines that support product or customer-facing systems (rather than solely internal analytics).

• Strong engineering foundation — proficient in production-grade Python, adept with SQL, and experienced in code review, testing, CI/CD, and operational ownership.

• Extensive cloud infrastructure expertise — AWS (S3, Kinesis/MSK, Lambda, ECS/EKS, IAM, networking) or a comparable platform; comfortable with infrastructure-as-code tools (Terraform, CDK, or similar).

• Experience in streaming or real-time data ingestion (Kafka, Kinesis, Flink, Spark Streaming, or similar) into a warehouse or lakehouse environment.

• A solid background with modern data warehouse/lakehouse technologies (Snowflake, BigQuery, Redshift, Databricks, Athena, or similar).

• Practical experience with data transformation tools, especially dbt.

• Proven track record of building and maintaining distributed data systems at scale — with a focus on performance, reliability, and cost efficiency.

• Familiarity with data quality and observability tools and practices (Great Expectations, dbt tests, Monte Carlo, or similar).

• Experience in enabling AI/ML workloads using production data.

• Excellent communication skills in English, both written and verbal, with the ability to collaborate effectively with engineering, product, and non-engineering stakeholders.

• Comfortable operating in a fully remote setting.

• Must be physically located within Europe.

• **Nice to have**

• Knowledge of data cataloging tools, data contract frameworks, or principles of data mesh.

• Experience in B2B SaaS and familiarity with intent data, web event data, CRM, product analytics, billing, and support tools.

🏝️ Benefits

• The opportunity to collaborate with a knowledgeable, high-achieving, and enjoyable team.

• An international, diverse, dynamic, and dedicated work atmosphere.

• Flexibility to work remotely, with a customizable work schedule.

• Mental health support provided by Auntie.