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The Applications Development Senior Programmer Analyst is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to contribute to applications systems analysis and programming activities.
Job Responsibility
Conduct tasks related to feasibility studies, time and cost estimates, IT planning, risk technology, applications development, model development, and establish and implement new or revised applications systems and programs to meet specific business needs or user areas
Monitor and control all phases of development process and analysis, design, construction, testing, and implementation as well as provide user and operational support on applications to business users
Utilize in-depth specialty knowledge of applications development to analyze complex problems/issues, provide evaluation of business process, system process, and industry standards, and make evaluative judgement
Recommend and develop security measures in post implementation analysis of business usage to ensure successful system design and functionality
Consult with users/clients and other technology groups on issues, recommend advanced programming solutions, and install and assist customer exposure systems
Ensure essential procedures are followed and help define operating standards and processes
Serve as advisor or coach to new or lower level analysts
Has the ability to operate with a limited level of direct supervision
Can exercise independence of judgement and autonomy
Acts as SME to senior stakeholders and /or other team members
Design, develop, and maintain high-performance data pipelines using Python and PySpark
Build and optimize ETL/ELT workflows for large-scale batch and streaming data
Write clean, reusable, testable, and well-documented Python code
Optimize Spark jobs for performance, memory usage, and cost efficiency
Implement data transformations, aggregations, and validations at scale
Work with structured and semi-structured data (Parquet, ORC, JSON, Avro, CSV)
Integrate with data sources such as RDBMS, NoSQL, cloud storage, and message queues
Ensure data quality, integrity, and governance across pipelines
Support migration and modernization of legacy data workflows to Spark-based architectures
Contribute to data architecture and design discussions
Review code and mentor junior developers
Collaborate with DevOps, Data Science, and Analytics teams
Participate in production support and performance tuning activities
Requirements
5-8 years of relevant experience
Experience in systems analysis and programming of software applications
Experience in managing and implementing successful projects
Working knowledge of consulting/project management techniques/methods
Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements
Strong expertise in Python (8+ years preferred)
Hands-on experience with Apache Spark / PySpark (4+ years)
Solid understanding of distributed computing concepts
Strong SQL skills and experience with relational databases
Experience with big data ecosystems (Hive, HDFS, Delta Lake, or similar)
Familiarity with cloud platforms (AWS / Azure / GCP) and cloud-native data services
Experience with job orchestration tools (Airflow, Oozie, Azure Data Factory, etc.)
Proficiency in Linux/Unix environments
Experience with CI/CD pipelines
Knowledge of unit testing, logging, monitoring, and debugging in distributed systems
Familiarity with Git and code versioning practices
Bachelor's degree/University degree or equivalent experience
Nice to have
Experience with Spark Structured Streaming
Knowledge of Kafka or other messaging systems
Exposure to ML pipelines or feature engineering using PySpark
Familiarity with data security, governance, and compliance standards
Experience leading or owning end-to-end data solutions
Prior experience in large enterprise or high-scale environments