SR. DATA ENGINEER (freelancer)

About the role

You’ll be responsible for designing and implementing scalable, high-performance data systems, while helping define best practices across the organization.

From building pipelines to enabling advanced analytics and ML use cases, your work will directly impact how we leverage data across global clients.

Responsibilities

• Design and implement scalable data architectures (ETL/ELT)

• Build and maintain data pipelines for ingestion, processing, and consumption

• Develop APIs and data services to support analytics and product use cases

• Work with AWS and/or Azure to deploy modern data platforms (data lakes, warehouses, streaming)

• Automate data workflows with a focus on resilience, observability, and performance

• Collaborate with Data Scientists, Analysts, and Product teams to bring models into production

• Participate in architecture decisions and code reviews

• Explore and implement emerging trends (Data Mesh, MLOps, RAG, etc.)

What we’re looking for

• 5–7+ years of experience in Data Engineering or backend/data-focused development

• Strong expertise in Python (Pandas, NumPy, SQLAlchemy)

• Advanced SQL skills (optimization, complex queries, performance tuning)

• Experience with Apache Spark and Airflow

• Solid experience with data warehouses (Snowflake, BigQuery, Redshift)

• Strong knowledge of AWS and/or Azure ecosystems

• Experience building production-ready pipelines with CI/CD and Docker

• Experience working in agile environments

✨ Nice to have

• Experience with Kafka or real-time streaming

• Knowledge of Scala or Java (for Spark)

• Experience with NoSQL databases (MongoDB, Redis, Cassandra)

• Familiarity with Kubernetes and Terraform

• Exposure to MLOps or AI systems (RAG, ML pipelines)

• Experience in startups or fast-paced environments

⚡️ Key skills

• Scalable architecture & performance optimization

• Strong problem-solving and systems thinking

• Ownership and autonomy

• Clear communication and ability to work cross-functionally