
Data Engineer
2 days ago
Responsibilities:
- Design and implement data migration, ingestion, processing, and analytics pipelines using AWS (S3, Glue, Lambda, Athena, RDS Aurora, Databricks) and Azure (ADF, ADLS, Synapse, Databricks).
- Apply strong expertise in SQL, data modeling, schema design, and data quality management.
- Ensure governance, security, compliance, metadata management, MDM, and data catalog practices.
- Work with big data, NoSQL, relational DBs, and data warehouse solutions.
- Build real-time pipelines with Kafka/Event Hubs and enable Data Fabric architecture with APIs, data virtualization, and lineage tools (Collibra, Informatica, Alation, Purview).
- Support CI/CD, DevSecOps, IaC (Terraform/Bicep), and Agile Scrum practices.
Required Skills & Qualifications:
- Lead Data Engineer: 810 years; Data Engineer: 68 years of experience.
- Proficiency in Apache Spark (PySpark/Scala), SQL, data pipelines, and cloud migration.
- Strong experience with Azure and AWS data services.
- Familiar with metadata management, lineage, governance tools, and schema registry.
- Good communication, teamwork, and problem-solving skills.
Preferred:
- Knowledge of microservices, event-driven architectures,
- Experience with SSIS, Hadoop ecosystem (Hive, HBase, Cassandra, Spark, Flume, Impala).
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