Mazo Solutions | Senior Data Engineer | india
2 days ago
Position Overview:
We are seeking a highly experienced Senior Data Engineer with 10+ years of expertise in designing, implementing, and optimizing data solutions. The ideal candidate will have a strong background in data pipelines, big data processing, and cloud-native solutions, ensuring seamless data availability and insights across the organization.
Key Responsibilities:
- Design and implement end-to-end data pipelines to support ETL/ELT workflows and ensure reliable data ingestion, transformation, and storage.
- Architect scalable and high-performance data solutions on cloud platforms such as AWS, Azure, or Google Cloud.
- Build, maintain, and optimize distributed data processing systems using frameworks like Apache Spark , Kafka , or Hadoop .
- Manage and enhance data warehouses, data lakes, and other data storage solutions to support analytics and machine learning initiatives.
- Develop real-time and batch data processing solutions, ensuring low-latency and high-throughput performance.
- Leverage advanced SQL and NoSQL databases (e.g., MySQL , PostgreSQL , MongoDB , DynamoDB , etc.) for data storage and analysis.
- Collaborate with data scientists, analysts, and business stakeholders to define data requirements and ensure alignment with business goals.
- Implement and advocate for best practices in data governance, quality, and security.
- Lead the development of tools for monitoring and managing data pipelines to ensure their reliability and performance.
- Mentor junior data engineers and provide leadership in technical design and strategy.
Skills Required:
- Programming Expertise: Python, Java, Scala, or similar languages for data engineering tasks.
- Big Data Tools: Proficiency in Apache Spark , Kafka , Hadoop , or similar technologies.
- Cloud Platforms: AWS (S3, Redshift, Glue, Lambda), Azure (Data Factory, Synapse), or Google Cloud (BigQuery, Dataflow).
- Database Management: Strong knowledge of both relational (e.g., MySQL, PostgreSQL) and non-relational databases (e.g., MongoDB, DynamoDB).
- Data Modeling: Deep understanding of dimensional modeling, star schema, and data normalization techniques.
- CI/CD: Experience in integrating data solutions with DevOps practices and tools.
- Data Governance: Knowledge of data privacy regulations (e.g., GDPR, CCPA) and implementation of governance frameworks.
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