Job Overview:
We are seeking a skilled Big Data Engineer to design, develop, and maintain scalable data processing systems. The ideal candidate will have expertise in big data technologies, ETL pipelines, cloud platforms, and distributed computing frameworks. You will collaborate with data scientists, analysts, and software engineers to optimize data workflows and ensure high-performance data solutions.
Key Responsibilities:
- Design, implement, and manage big data architectures to handle large-scale data processing.
- Develop ETL pipelines to ingest, transform, and store structured and unstructured data.
- Optimize and maintain data lakes, data warehouses, and real-time processing frameworks.
- Work with Apache Spark, Hadoop, Kafka, and other big data technologies to process massive datasets.
- Implement data security, governance, and compliance best practices.
- Collaborate with cross-functional teams to integrate big data solutions into business applications.
- Monitor and troubleshoot performance issues related to data pipelines and distributed systems.
- Automate data workflows and build scalable solutions for data ingestion and processing.
Required Skills & Qualifications:
- Bachelor’s/Master’s degree in Computer Science, Data Engineering, or a related field.
- Proven experience in Big Data frameworks (Hadoop, Spark, Hive, HBase, Flink, or Storm).
- Strong expertise in SQL and NoSQL databases (MongoDB, Cassandra, PostgreSQL, etc.).
- Experience with cloud platforms like AWS (Glue, EMR, Redshift), Azure (Databricks, Synapse), or Google Cloud (BigQuery, Dataflow).
- Proficiency in Python, Scala, Java, or SQL for data processing.
- Experience with real-time data streaming technologies (Kafka, Kinesis, Pub/Sub).
- Strong understanding of data modeling, ETL development, and data pipeline optimization.
- Knowledge of containerization (Docker, Kubernetes) and DevOps for data pipelines is a plus.
- Familiarity with CI/CD tools and automation techniques.
- Excellent problem-solving and analytical skills.
Preferred Qualifications:
Knowledge of data governance frameworks and compliance (GDPR, HIPAA).
Certifications in AWS, GCP, or Azure big data technologies.
Experience with machine learning pipelines and AI-driven analytics.
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