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We are seeking a highly experienced, strategic, and technically proficient Senior Lead Big Data Developer (C13) to drive the development, standardization, and governance of data across our Big Data Portfolio. This role is crucial in enabling enterprise-wide data consistency, ensuring adherence to industry data standards, and optimizing data pipelines for high-performance applications.
Job Responsibility:
Lead the design, development, and optimization of scalable, standardized, and high-performance data architectures
Define and implement data standardization frameworks, metadata management, and data governance principles across multiple projects
Collaborate with business, compliance, risk, and regulatory teams to ensure data meets industry standards (ISO, FIBO, BCBS 239, etc.)
Drive data lineage, data quality, and reconciliation strategies to improve data reliability and accessibility
Architect and optimize data pipelines (ETL/ELT) with streaming and batch processing methodologies
Partner with cross-functional teams to automate data reconciliation, validation, and anomaly detection
Implement data security and privacy controls in compliance with internal policies and external regulations
Mentor and guide junior and mid-level engineers while fostering a culture of engineering excellence and continuous learning
Own end-to-end data lifecycle management, ensuring seamless ingestion, processing, and storage of structured and unstructured data
Requirements:
10+ years of experience in data engineering, software development, and Big Data platforms
Expertise in Java, J2EE, Springboot, Micro Services, Big Data technologies (Spark, Hadoop, Hive, Impala, Kafka, Scala, Cloudera, Databricks)
Hands-on experience in data standardization, data governance, and metadata management
Strong SQL and NoSQL database expertise (Oracle, MongoDB, Couchbase)
Proficiency in Python, Java, and Shell scripting for data processing and automation
Deep understanding of data modeling, data lineage, and ETL frameworks
Knowledge of cloud-based data solutions (AWS, GCP, or Azure)
Familiarity with machine learning-based anomaly detection and automated reconciliation frameworks
Experience in Capital Markets, Risk, Finance, and Regulatory Reporting is a plus
Agile leadership experience, with the ability to drive data initiatives in an Agile/DevOps environment
Strong analytical and problem-solving skills with a data-driven mindset
Nice to have:
Expertise in Canonical Data Models and Data Mesh Architecture
Experience working with ISO standards for financial data interoperability
Ability to influence senior stakeholders and drive data-driven decision-making
Strong documentation and technical storytelling skills for presenting data strategies
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