Offer summary

Qualifications:

Minimum 6 years of experience as a Data Engineer with large-scale data architectures., Strong expertise in SQL and advanced proficiency in Python for ETL and data automation., In-depth experience with Apache Spark and Kafka for big data processing and real-time data streaming., BSc in Computer Science, Data Engineering, or a relevant field..

Key responsibilities:

Design, build, and manage ETL/ELT pipelines using tools like AWS Glue and Azure Data Factory.

Develop scalable real-time and batch data processing solutions using Apache Spark and Kafka.

Collaborate with data analysts and engineers to define data models and ensure data integrity throughout the pipeline.

Monitor and troubleshoot pipeline performance and automate workflows in cloud-native environments.

Job description

Company Overview

At SPACE44, we empower tech startups and innovative companies across the US and Europe by delivering top-tier software engineers and comprehensive HR solutions. Unlike traditional staffing agencies, we accelerate innovation by providing performant hiring pipelines, efficient onboarding processes, performance management, and administrative assistance as an end-to-end service. Our unique approach ensures precise integration and high team performance in full-remote, nearshore, and offshore settings.

We enhance your work-life balance by offering opportunities that align your personal and professional aspirations. Work remotely to seamlessly integrate your career with your lifestyle and bring everything into a flow. We offer you a dynamic and supportive environment where you can develop and grow. Join a forward-thinking team that values the joy of work, openness, and cross-cultural collaboration. At SPACE44, let's shape the future of modern work together.

Who We Are Looking For?

We’re building our talent pool of outstanding Data Engineers for upcoming client projects. This is not an active position tied to a current project, but a proactive opportunity to become part of our expert network at SPACE44. When a suitable project arises, you'll be among the first we reach out to.

We’re always on the lookout for professionals who bring deep expertise, remote collaboration experience, and a passion for shaping the future of software and product development. If you enjoy solving complex problems and want to be considered for impactful future roles, we’d love to connect.

Key Responsibilities:

Design, build, and manage ETL/ELT pipelines using tools like AWS Glue, Azure Data Factory, and Apache Airflow
Develop scalable real-time and batch data processing solutions using Apache Spark and Kafka
Write optimized, production-grade SQL queries and perform performance tuning across data systems
Build and maintain data lakes and warehouses, including platforms like Snowflake and BigQuery
Work with structured and semi-structured data across relational and NoSQL databases (e.g., MongoDB, Cassandra)
Collaborate with data analysts, engineers, and product teams to define data models and architecture
Ensure data integrity, quality, and lineage throughout the pipeline
Automate workflows, testing, and deployment for data systems in cloud-native environments
Monitor and troubleshoot pipeline performance and reliability

Requirements:

Minimum 6 years of experience as a Data Engineer working with large-scale data architectures
Strong expertise in SQL for data manipulation, optimization, and analytics
Advanced proficiency in Python for ETL, scripting, and data automation
In-depth experience with Apache Spark for big data processing and distributed computing
Proven experience with Kafka for real-time data streaming and event processing
Hands-on experience with cloud-native ETL tools such as AWS Glue and Azure Data Factory
Familiarity with data warehousing platforms like Snowflake or BigQuery
Knowledge of NoSQL databases like MongoDB or Cassandra
Comfortable working in modern cloud environments and Agile remote teams
BSc in Computer Science, Data Engineering, or a relevant field

Nice to Have:

Experience with Apache Airflow or similar orchestration frameworks
Familiarity with GCP tools like BigQuery or Dataflow
Exposure to legacy big data systems such as Hadoop in hybrid environments
Understanding of data governance, security, and compliance in cloud data workflows
Knowledge of data modeling techniques for both OLAP and OLTP use cases
Interest in emerging technologies in real-time analytics and data mesh architecture

Embark on your SPACE44 journey with a few simple steps:

Hireflix Chat (20 min): Share how you work and what matters most to you
HR Sync (45 min): Connect your experience with our goals
Psychometric Insight: Take a 1-hour assessment exploring your strengths and working style

Benefits

Flexible Work Schedule: Enjoy a non-linear workday designed to enhance productivity and maintain a harmonious work-life balance, with core hours for team collaboration.
Professional Growth: Access advanced training opportunities in data science and machine learning to boost your career prospects.
Innovative Projects and Tools: Engage in cutting-edge projects using the latest tools and technologies within a progressive remote work environment.
Competitive Income: Receive a competitive income with regular performance reviews and potential raises every six months.
Global Team Dynamics: Collaborate with a diverse, international team that values openness and teamwork.

Required profile