Senior Data Engineer, Platform Data
New
L
LeadfeederB2B SaaS
GermanyFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 10+ years
- Required Skills
- AWSPythonSQLKafkaSnowflakeData engineeringCI/CDTerraformdbt
Requirements
- 10+ years of hands-on experience in data and/or software engineering, with a leading role in production data pipelines.
- Strong engineering background with production-grade Python, SQL, code review, testing, and CI/CD.
- Deep cloud infrastructure experience in AWS (S3, Kinesis/MSK, Lambda, ECS/EKS, IAM, networking) or equivalent.
- Proficiency in infrastructure-as-code tools such as Terraform or CDK.
- Experience with streaming or real-time data ingestion systems like Kafka, Kinesis, Flink, or Spark Streaming.
- Solid experience with modern data warehouse or lakehouse technologies like Snowflake, BigQuery, Redshift, or Databricks.
- Hands-on experience with data transformation tooling, particularly dbt.
- Track record of building and operating distributed data systems at scale with focus on performance, reliability, and cost.
- Familiarity with data quality and observability practices using tools like Great Expectations or Monte Carlo.
- Background in enabling AI/ML workloads on top of production data.
- Strong communication skills in English to collaborate with engineering and product stakeholders.
- Must be physically located within Europe.
Responsibilities
- Design, build, and operate production data pipelines that power Leadfeeder's product features.
- Build and maintain streaming and real-time ingestion systems that move event data through the platform at scale.
- Own the cloud infrastructure underpinning the pipelines, including compute, storage, and networking managed as code.
- Collaborate with product and ML engineers to deliver datasets that power product-facing features and AI/ML workflows.
- Implement data quality, observability, and reliability controls to ensure data trust and system uptime.
- Drive engineering practices including code reviews, testing, CI/CD, and performance tuning.
- Partner with cross-functional teams to translate requirements into scalable data systems.
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