- Company Name
- RAVL
- Job Title
- Data Engineer
- Job Description
-
**Job Title:** Data Engineer
**Role Summary:**
Design, develop, and operate scalable data pipelines and platforms that transform raw data into reliable, high‑quality assets. Enable insights, analytics, and machine‑learning workloads across modern cloud environments, ensuring performance, security, and governance.
**Expectations:**
- Build robust, scalable ETL/ELT pipelines using cloud‑native tools.
- Develop data models and architectures that support efficient analytics and reporting.
- Integrate data flows with application ecosystems and maintain observability, reliability, and governance.
- Mentor peers, contribute to data‑architecture decisions, and influence cross‑team standards.
**Key Responsibilities:**
- Design, implement, and maintain end‑to‑end data pipelines (ETL/ELT).
- Create and optimize data models for analytics, reporting, and ML purposes.
- Perform data ingestion, transformation, extraction, loading, and quality checks from multiple sources.
- Leverage cloud services (AWS, Azure, GCP) to build secure, cost‑efficient data systems.
- Work with platform and software engineers to embed data flows in broader applications.
- Ensure observability, reliability, and governance across all data products.
- Collaborate with analysts, architects, and stakeholders to translate business requirements into technical solutions.
**Required Skills:**
- **Languages:** Python, SQL; Java or Scala preferred.
- **Data Processing & Orchestration:** Apache Spark, Airflow, dbt, Kafka, or similar.
- **Cloud Platforms:** AWS (Glue, Redshift), Azure (Data Factory, Synapse), GCP (BigQuery, Dataflow); experience with at least two platforms.
- **Data Warehousing & Lakehouse:** Snowflake, Redshift, BigQuery, Databricks, Delta Lake.
- **CI/CD & Automation:** GitHub Actions, Jenkins, Azure DevOps for data workflows.
- **Security & Compliance:** IAM, encryption, access control, secure data handling.
- **Governance:** Data cataloging, metadata management, and best practices in data security.
- **Consulting & Communication:** Clear, concise communication, stakeholder management, and adaptability.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent professional experience.
- Relevant cloud or data engineering certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate, GCP Professional Data Engineer) are advantageous but not mandatory.