JIMMY LAMBA

• Spearheaded delivery management for multiple platform portfolios
• Led program planning, execution, and collaboration with Australian team for enterprise platform and product changes.
• Headed requirement workshops, technical designs, and project deliverables across various levels and divisions.
• Supported program decisions by identifying innovative solutions to project deadlocks, resolving issues, and identifying synergies between teams.
• Collaborated with cross-functional teams to provide tailored Agile implementations and align with release cadence.
• Drove projects for infrastructure upliftment and technology upgrades across platform.
• Responsible for Proof of Concept (POC) programs and adoption of new technologies such as Terraform and centralized logging.
• Chartered to build data products for stores, enabling predictive inventory visibility, real-time reporting of variable demand, and improved inventory accuracy using RFID technology.
• Built cloud-native data lake infrastructure platform on Snowflake, designing, implementing, and managing data warehousing solutions on Snowflake Data Cloud platform.
• Architected scalable and efficient data models to support business reporting and analytics requirements, resulting in improved data accessibility and performance.
• Deployed and managed Docker containers in production environments, leveraging Kubernetes for container orchestration and scaling.
• Successfully implemented dbt (data build tool) to streamline and accelerate code development for data transformations and analytics within Snowflake data warehouse environment.
• Utilizing advanced analytics and real-time insights from digital footprint of data in Snowflake, we achieved 50% reduction in CODB

• Designed and implemented scalable data architecture solutions tailored to meet specific business requirements and support strategic initiatives.
• Evaluated and adopted new data technologies and tools to enhance data management capabilities, driving innovation within the organization.
• Spearheaded the design and development of a robust framework for projects utilizing Spark 2.4 and Python 3.6, enabling dynamic configuration file reading and data processing from multiple sources to multiple target sinks.
• Led the design and implementation of event stream handling, leveraging Spark transformations to optimize data processing workflows.
• Managed the ingestion, processing, and output of data from Kafka Data Streams using Spark Structured Streaming, ensuring efficient and real-time data processing.
• Streamlined infrastructure provisioning and project deployment processes through orchestrating EMR Cluster creation with Terraform and optimizing project delivery workflows via Jenkins Pipelines.
• Conducted performance tuning of Spark jobs to optimize data processing efficiency for handling high volumes of data, improving overall system performance and responsiveness.

• Implemented multi-node clusters in Hortonworks on-premises data centers as well as cloud platforms.
• Designed end-to-end architecture flow for the entire process, including data extraction, transformation, loading, analysis, and visualization.
• Facilitated data import and export between HDFS and Hive using Sqoop to ensure seamless data integration and accessibility.

• Wrote software that scaled to petabytes of data and supported millions of transactions per second.
• Partnered with infrastructure engineers and system administrators in designing big-data infrastructures.
• Acted as expert technical resource to programming staff in program development, testing and implementation process.

• Led requirement gathering efforts and designed logical and physical data models, facilitating seamless integration of diverse data sources.

• Utilized Hortonworks frameworks extensively for infrastructure management and optimization.

• Prepared detailed LLDs, HLDs, and functional specifications, ensuring alignment with project objectives and ETL specifications.

• Implemented complex logic for customer data linkage using various identifiers like mobile numbers, emails, and social media handles, leveraging Amazon S3, Redshift for data management and processing.

• Implemented MapReduce algorithms using Java, PIG, and Hive to meet client requirements.
• Developed User Defined Functions (UDFs) in Hive using Java and optimized MapReduce programs for enhanced performance.
• Designed and executed Hive queries and UDFs to parse raw data, loading it into partitioned Hive tables.

● Worked on Big Data Engineering and Data Ingestion Project for Banking and Financial Services company.

● Getting real time streaming data from Traditional Messages Queues and Ingesting data into Kafka

● Parsing the Semi Structured data using Real time Processing Framework Storm and inserting data

• Prepared high-level design documents and detailed low-level design documents outlining the architecture and functionality of the solution.

• Established ETL standards and naming conventions, and documented ETL flow processes for staging, operational data store (ODS), and data marts.

• Designed and implemented Informatica mappings and sessions in accordance with business rules and requirements to efficiently load data from various sources into target tables.

• Developed complex Informatica mappings for data loading from multiple sources using various transformations including source qualifier, lookup, expression, aggregator, joiner, filter, and router
• Utilized Informatica PowerCenter tools such as source analyzer, mapping designer, mapplet, and transformations for efficient data processing
• Proficient in relational database development using PL/SQL and SQL across various platforms including Oracle, SQL Server, and DB2.