
Highly Skilled Data Specialist
5 days ago
We are seeking a highly skilled data professional to join our team as a Big Data Developer.
Job Description:
The successful candidate will be responsible for designing, building and maintaining robust data pipelines that handle high-volume financial data. Key responsibilities include:
- Design, develop and manage end-to-end data pipelines for stocks, crypto and other financial datasets.
- Integrate third-party APIs and data feeds into internal systems.
- Build and optimize data ingestion, storage and transformation workflows (batch and real-time).
- Ensure data quality, consistency and reliability across all pipelines.
- Collaborate with data scientists, analysts and backend engineers to provide clean, structured and scalable datasets.
- Monitor, troubleshoot and optimize pipeline performance.
- Implement ETL/ELT best practices, data governance and security protocols.
- Contribute to the scalability and automation of our data infrastructure.
Requirements:
- Proven experience as a Big Data Engineer/Data Engineer (preferably in financial or crypto domains).
- Strong expertise in Python, SQL and distributed data systems.
- Hands-on experience with data pipeline tools (e.g., Apache Spark, Kafka, Airflow, Flink, Prefect).
- Experience with cloud platforms (AWS, GCP or Azure) and data warehousing (Snowflake, BigQuery, Redshift etc.).
- Knowledge of API integrations and handling real-time streaming data.
- Familiarity with databases (relational and NoSQL) and data modeling.
- Solid understanding of stocks, cryptocurrencies and financial data structures (preferred).
- Strong problem-solving skills with the ability to handle large-scale data challenges.
Benefits:
This role offers excellent opportunities for growth and development, with a focus on innovation and collaboration. As a key member of our team, you will have access to cutting-edge technologies and tools, as well as ongoing training and support.
What We Offer:
Competitive salary package, bonus scheme and benefits program.
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