Data Engineer

RocketDevs empowers software engineers by bridging talent with global tech opportunities. We connect skilled developers with innovative projects, fostering an inclusive tech community.

We are seeking a talented Data Engineer to join our team and contribute to client projects that drive data-driven decision-making and technological advancement. This is a remote position focused on building robust data pipelines and scalable data systems for our global clients.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows.
• Develop and manage data architectures, including data lakes, warehouses, and streaming systems.
• Work with both structured and unstructured data across SQL and NoSQL systems.
• Optimize data storage, retrieval, and processing for performance and scalability.
• Integrate data from various sources (APIs, third-party services, internal systems).
• Ensure data quality, integrity, and reliability across pipelines.
• Collaborate with data scientists, analysts, and engineers to support data use cases.
• Explore opportunities to leverage AI tools to improve data workflows or insights generation.
• Implement monitoring, logging, and alerting for data systems.
• Participate in architecture discussions, code reviews, and sprint planning.

Qualifications

• Strong proficiency in Python or another data-focused language (e.g., Scala, Java).
• Experience with sp
• Experience building and maintaining ETL/ELT pipelines.
• Solid understanding of SQL and experience with relational databases (e.g., PostgreSQL, MySQL).
• Experience with NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB).
• Familiarity with data warehousing solutions (e.g., BigQuery, Redshift, Snowflake).
• Experience with distributed data processing tools (e.g., Apache Spark, Kafka, Flink).
• Knowledge of REST APIs and data integration techniques.
• Familiarity with cloud platforms (AWS, GCP, or Azure).
• Experience with version control (Git & GitHub), CI/CD pipelines, and containerization (Docker).
• Understanding of data modeling, schema design, and data governance principles.
• A deployed project or pipeline (personal or professional) demonstrating real-world data engineering work is required.

Nice to Have

• Experience with orchestration tools (e.g., Airflow, Prefect, Dagster).
• Familiarity with real-time data streaming architectures.
• Experience with data observability and monitoring tools.
• Exposure to AI/ML pipelines or feature engineering workflows.
• Familiarity with vector databases or embeddings for AI-powered applications.
• Knowledge of tools like dbt for data transformation.
• Experience optimizing data costs and query performance in cloud environments.
• Experience Data visualization tools (e.g Tableau, Power BI)

Hiring Process

We ensure a fair and transparent process for every applicant:

Apply → Take a Compulsory 30-minute Assessment → 30-minute Onboarding Interview → Final interview & selection

Note:

• The assessment is mandatory. Please apply only if you’re willing to take it.
• Having a deployed project (personal or professional) that demonstrates your ability to build and manage real-world data systems is a must.

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