Senior Software Engineer, Data Platform

Jobtailor; Deutschland; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

Jobtailor is seeking an experienced Data Platform Engineer to design and operate scalable analytics data services. You will own ingestion pipelines, data models, and analytics warehousing, enabling analytics, reporting and ML workloads across products.

The role emphasizes Go (preferred) or other strong typed languages, Python, and cloud (GCP). You will influence architecture, governance, and security in a multi-tenant SaaS environment, with opportunities for impact across release cycles.

Qualifikationen

• 5+ years in scalable distributed systems, data platforms or backend services in production.
• Strong SQL skills with data modeling, queries and analytics workloads.
• Go backend experience; Python proficiency desired.
• Cloud platform experience, ideally Google Cloud (GCP).
• Experience with ClickHouse, internals, materialized views and OLAP workloads.
• Experience designing/operating large-scale ingestion pipelines (Kafka, Pulsar, CDC).
• Familiarity with Debezium, Flink, Dataflow or similar streaming frameworks.
• Experience with multi-tenant SaaS platforms, data governance and IaC (Terraform).
• Experience with analytical/time-series DBs such as PostgreSQL/TimescaleDB.
• Exposure to AI-powered apps/LLM integrations is a plus.

Aufgaben

• Design and build scalable data platform services powering analytics, reporting, ML, and AI workloads.
• Build and maintain reliable data ingestion pipelines using CDC and event-driven architectures.
• Develop and evolve centralized analytics warehouse for performance and scalability.
• Design data models, materialized views, and aggregation strategies for product analytics and reporting.
• Build APIs and services exposing analytics and reporting to internal/external consumers.
• Define multi-tenant security controls, data governance, and access management policies.
• Monitor platform health, data freshness, ingestion lag, and reliability.
• Contribute to technical specs and participate in architecture discussions.
• Improve developer productivity through automation, tooling, observability, and ops excellence.
• Strengthen test coverage and engineering practices for reliable systems.

Kenntnisse

Go

Python

SQL

Cloud GCP

ClickHouse

Kafka/Pulsar

Data Modeling

Timeseries DBs

On-call

Team Collaboration

Tools

Debezium

Flink

Dataflow

Terraform

PostgreSQL

TimescaleDB

Jobbeschreibung

Responsibilities

• Design and build scalable data platform services that power analytics, reporting, machine learning, and AI workloads across Maropost products.
• Build and maintain reliable data ingestion pipelines using CDC and event-driven architectures.
• Develop and evolve our centralized analytics warehouse, ensuring high performance, scalability, and maintainability.
• Design and implement data models, materialized views, and aggregation strategies to support product analytics and business reporting.
• Build supporting APIs and services that expose analytics and reporting capabilities to internal and external consumers.
• Define and implement multi-tenant security controls, data governance standards, and access management policies.
• Monitor platform health, data freshness, ingestion lag, and overall system reliability.
• Contribute to technical specifications and actively participate in architecture and design discussions.
• Improve developer productivity through automation, tooling, observability, and operational excellence.
• Strengthen test coverage and engineering practices to ensure reliable and maintainable systems.

Requirements

• 5+ years of hands-on software engineering experience building and operating highly scalable distributed systems, data platforms, or backend services in production.
• Strong experience with modern analytical data warehouses such as ClickHouse, BigQuery, Snowflake, or Amazon Redshift.
• Deep expertise in ClickHouse, including internals, materialized views, and OLAP workload optimization, is a plus.
• Experience designing and operating large-scale data ingestion pipelines using Kafka, Pulsar, CDC-based architectures, and related streaming technologies.
• Familiarity with tools such as Debezium, Flink, Dataflow, or similar streaming and data processing frameworks is preferred.
• Strong SQL skills with hands-on experience in data modelling, query optimization, and analytical workloads.
• Experience working on data platforms, data engineering, or analytics engineering initiatives involving large-scale data processing and transformation workloads.
• Experience building and maintaining backend services in Go (preferred) or another modern strongly typed programming language, along with proficiency in Python.
• Experience with cloud platforms, preferably GCP, including managed data, messaging, and observability services.
• Experience owning and delivering production systems end-to-end, from technical design and stakeholder discussions through deployment, operational support, and iterative improvements across multiple release cycles.
• Experience with multi-tenant SaaS platforms, data governance practices, data security controls, and infrastructure-as-code tools such as Terraform.
• Experience with analytical and time-series databases such as PostgreSQL, TimescaleDB, or similar technologies.
• Exposure to AI-powered applications, LLM integrations, or agentic workflows is an added advantage.
• Comfortable participating in on-call rotations and focused on building simple, efficient solutions without over-engineering.
• Proactive and self-driven, with strong problem-solving and communication skills, and the ability to collaborate effectively with both technical and non-technical stakeholders.