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Data Engineer

Huzzle · Germany · Remote

  • Employment typeFull-time
  • Experience levelMid level
  • Salary signalSalary not listed
  • Last checked7 hours ago
  • Source valid throughDec 7, 2026

Role Overview

About Huzzle At Huzzle, we connect exceptional talent with exciting opportunities at leading companies across the UK, US, Canada, Europe, and Australia. We work with a diverse range of clients, including startups, digital agencies, and technology-driven businesses across industries such as SaaS, MarTech, FinTech, and AI. Unlike traditional outsourcing agencies, we place you directly with our clients, where you become an integral, in-house member of their team. Job Type: Full-time Location: Remote Job Summary As a Data Engineer, you will play a key role in designing, developing, and maintaining scalable data pipelines and infrastructure. You will collaborate with data analysts, data scientists, software engineers, and business stakeholders to ensure data is reliable, accessible, and of high quality across the organisation. This is a great opportunity for professionals who enjoy tackling complex data challenges and building robust systems that power business intelligence, analytics, and machine learning initiatives. Key Responsibilities Design, build, and maintain scalable ETL and ELT data pipelines. Develop and optimize data architectures, databases, and data warehouses. Integrate data from various sources, APIs, and third-party platforms. Maintain data quality, accuracy, consistency, reliability, and security. Monitor, troubleshoot, and improve data pipelines and workflows. Work closely with analytics, engineering, and business teams to identify and meet data requirements. Establish data governance standards and best practices for data management. Improve data storage, processing speeds, and query performance. Support business intelligence, reporting, and analytics projects. Maintain documentation of data models, workflows, and technical processes. Requirements 2+ years of experience in data engineering, data warehousing, or a similar field. Strong SQL skills and a solid understanding of database management. Proficiency in Python, Java, Scala, or other relevant programming languages. Practical experience with ETL/ELT tools and building data pipelines. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform. Hands-on experience with modern data warehouse solutions such as Snowflake, Redshift, BigQuery, or Databricks. Knowledge of workflow orchestration tools such as Airflow or Prefect. Understanding of data modelling, governance, and data quality best practices. Experience handling large datasets and working with distributed systems is an advantage. Strong analytical thinking, problem-solving, and communication abilities. Comfortable working independently while collaborating with a remote team. Benefits 💰 Competitive compensation: Tailored to your experience, technical skills, and location. 🌎 Fully remote work: Enjoy the flexibility to work from anywhere. 🚀 Career development: Join innovative companies and contribute to meaningful, high-impact projects. 📈 Long-term potential: Grow your career alongside ambitious, expanding global organisations. 🧠 Ongoing learning: Gain exposure to emerging data technologies, cloud platforms, and large-scale data environments. 🤝 Collaborative environment: Work with skilled engineers, analysts, and business stakeholders. ⚙️ Modern tech stack: Work with cutting-edge data tools, technologies, and cloud-based solutions. Find Jobs in Germany on Arbeitnow

Why It Matches

This full-time role is listed as remote in Germany. The source does not expose a salary range, so confirm compensation before investing in a long application. The match score reflects role clarity, work mode, location, freshness, salary visibility, and description depth—not a promise that the employer will select a candidate.

Questions to Check Before Applying

  • Does the source describe the same title, company, location, and work arrangement shown here?
  • Which required skills can you prove with a result, project, metric, or certification?
  • Is remote eligibility limited by state, country, time zone, or travel expectations?
  • When will the employer disclose the salary range and total compensation?

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