Sr. Data Engineer

Fulcrum Digital is an agile and next-generation digital accelerating company providing digital transformation and technology services right from ideation to implementation. These services have applicability across a variety of industries, including banking & financial services, insurance, retail, higher education, food, health care, and manufacturing.

The Role

• Designing and building optimized data pipelines using cutting-edge technologies in a cloud environment to drive analytical insights.
  
• Constructing infrastructure for efficient ETL processes from various sources and storage systems.
  
• Leading the implementation of algorithms and prototypes to transform raw data into useful information.
  
• Architecting, designing, and maintaining database pipeline architectures, ensuring readiness for AI/ML transformations.
  
• Creating innovative data validation methods and data analysis tools.
  
• Ensuring compliance with data governance and security policies.
  
• Interpreting data trends and patterns to establish operational alerts.
  
• Developing analytical tools, programs, and reporting mechanisms.
  
• Conducting complex data analysis and presenting results effectively.
  
• Preparing data for prescriptive and predictive modeling.
  
• Continuously exploring opportunities to enhance data quality and reliability.
  
• Applying strong programming and problem-solving skills to develop scalable solutions.

Requirements

• High proficiency in Scala/Java and Spark for applied large-scale data processing.
  
• Expertise with big data technologies, including Spark, Data Lake, and Hive.
  
• Solid understanding of batch and streaming data processing techniques.
  
• Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.
  
• Expert-level ability to write complex, optimized SQL queries across extensive data volumes.
  
• Experience on HDFS, Nifi, Kafka.
  
• Experience on Apache Ozone, Delta Tables, Databricks, Axon(Kafka), Spring Batch, Oracle DB
  
• Familiarity with Agile methodologies.
  
• Obsession for service observability, instrumentation, monitoring, and alerting.
  
• Knowledge or experience in architectural best practices for building data lakes.