Mazo Solutions | Senior Data Engineer | india

3 days ago


Delhi, India Mazo Solutions Full time
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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