Staff Data Analytics Engineer

adsquare GmbH
Hennigsdorf, Germany
7 days ago
Apply on www.stepstone.de
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours

Tech stack

Clean Code Principles Java (Programming Language) Airflow Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 Data Analysis Big Data C++ (Programming Language) Profiling Computer Programming Continuous Integration
+22 more
Data Architecture Information Engineering Data Systems Data Warehousing Jinja (Template Engine) Python (Programming Language) Object-Oriented Software Development Mockito Software Engineering SQL Databases Test-Driven Development (TDD) Snowflake Apache Spark AWS Lambda Backend Kotlin Pyspark AWS Fargate Functional Programming Terraform Amazon Elastic Mapreduce (EMR) Golang

Job description

  • Technical Leadership & Architecture: Act as the principal architect for your squad. You will design horizontally scalable, cost-efficient, production-grade data solutions capable of handling TB-scale, highly dimensional datasets.

Requirements

  • Engineering Excellence & TDD: Champion rigorous software engineering principles. You will lead the adoption of Test-Driven Development (TDD), CI/CD workflows, and clean code architectures. You ensure our codebase is resilient, testable, and maintainable.\n, * 7+ years of experience in Data Engineering, Analytics Engineering, or Backend Development with a deep focus on massive data systems.\n
  • Geo-Spatial & Time-Series Expertise: Proven, hands-on experience handling massive datasets specifically involving geo-spatial (GIS) data, audience attributes, and high-frequency time-series data.\n
  • Advanced Software Engineering (Python): Mastery of Python beyond standard data scripting. You write highly modular, object-oriented code. You have deep, practical experience with Test-Driven Development (TDD), mocking, exception handling, and performance profiling, functional programming.\n
  • Architectural Vision: Deep expertise in designing scalable data architectures using both relational and horizontally scalable data warehouses/lakehouses (e.g., Snowflake, Redshift, Athena, StarRocks, Iceberg). You deeply understand query execution plans, partitioning, clustering, and cloud cost governance.\n
  • Big Data Frameworks: Extensive experience with large-scale data processing frameworks (e.g., Apache Spark, PySpark, AWS EMR, Glue) to handle massive throughput.\n
  • Expert SQL & dbt: You design scalable, robust data models (using Jinja, macros, incremental strategies) that serve as the foundation for our entire analytics layer.\n
  • AWS Cloud Native & IaC: Hands-on experience building architectures in AWS (e.g.: AWS Lambda, AWS Batch, Glue, StepFunctions, S3, EC2, ECS, ECR, Fargate) and deploying them using Infrastructure as Code (Terraform).\n
  • Leadership Skills: Superb organizational and communication skills. You can distill complex architectural trade-offs for non-technical stakeholders and drive technical consensus among your engineering peers.\n, * Polyglot Programming: Experience with a compiled or strongly typed language (e.g., Scala, Go, Kotlin, C++ or Java).\n
  • Advanced Orchestration: Experience defining complex dependency graphs in tools like Airflow, Dagster, or Prefect.\n

Benefits & conditions

  • Cross-Squad Impact: Drive technical alignment beyond your immediate team. You will act as an engineering ambassador, solving architectural issues that span multiple squads, keeping our technical processes synchronized, and aligning your squad’s work with global engineering priorities.\n
  • Domain Mastery: Leverage your deep expertise to build high-value data products on top of location signals and audience attributes. You don’t just process data; you deeply understand its geographic and time-series nature to unlock its business value.\n
  • Mentorship & Code Quality: Be the technical mentor for Senior, Mid, and Junior engineers. Through highly insightful code reviews, architectural feedback, and pair programming, your input will consistently be the source of others’ learning and growth.\n
  • Data Observability: Proactively build monitoring and alerting frameworks at the infrastructure level to catch anomalies in our multi-terabyte data streams before they impact downstream products.\n

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Your profile

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Your Profile \n

We are looking for an exceptional engineer who has a proven track record of acting as a technical leader and domain expert in heavy data environments. \n

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