The Senior Big Data engineering lead will play a pivotal role in designing, implementing, and optimizing large-scale data processing and analytics solutions. This role requires a visionary leader who can drive innovation, define architecture strategy, and ensure the scalability and efficiency of our big data infrastructure.
- Key Responsibilities
- Lead the design and development of a robust and scalable big data architecture handling exponential data growth while maintaining high availability and resilience.
- Design complex data transformation processes using Spark and other big data technologies using Scala, Pyspark
- Design and implement data pipelines that ensure data quality, integrity, and availability.
- Collaborate with cross-functional teams to understand business needs and translate them into technical requirements.
- Evaluate and select technologies that improve data efficiency, scalability, and performance.
- Oversee the deployment and management of big data tools and frameworks such as Hadoop, Spark, Kafka, and others.
- Provide technical guidance and mentorship to the development team and junior architects.
- Continuously assess and integrate emerging technologies and methodologies to enhance data processing capabilities.
- Optimize big data frameworks, such as Hadoop, Spark, for performance improvements and reduced processing time across distributed systems.
- Innovate in designing, developing, and refining data pipeline architectures to enhance data flow and ensure data processing capabilities.
- Implement data governance frameworks to ensure data accuracy, consistency, and privacy across the organization, leveraging metadata management and data lineage tracking.
- Conduct benchmarking and stress testing of big data solutions to validate performance standards and operational capacity.
- Ensure compliance with data security best practices and regulations.
Qualifications:
- Bachelor's or Master’s degree in Computer Science, Information Technology, or related field.
- Atleast 8-10 years overall software development experience on majorly working with handling application with large scale data volumes from ingestion, persistence and retrieval.
- Deep understanding of big data technologies, including Hadoop, Spark, Kafka, Flink, NoSQL databases, etc.
- Experience with Bigdata technologies Developer Hadoop , Apache Spark ,Python, PySpark
- Strong programming skills in languages such as Java, Scala, or Python.
- Excellent problem-solving skills with a knack for innovative solutions.
- Strong communication and leadership abilities.
- Proven ability to manage multiple projects simultaneously and deliver results.
Preferred Skills:
- Experience with data modeling and ETL/ELT processes.
- Experience in moving ETL frameworks from proprietary ETL technologies like Abinitio to Apache Spark
- Familiarity with machine learning and data analytics tools.
- Knowledge of core banking/financial services systems
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Job Family Group:
Technology
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Job Family:
Applications Development
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Time Type:
Full time
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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