USPB MIS Reporting – Re-Engineering

We are seeking an exceptionally skilled and experienced Lead Data Engineer to spearhead the re-engineering and automation of our Management Information Systems (MIS) reporting processes. The ideal candidate will possess deep expertise in data engineering, automation, and Big Data technologies, particularly SAS and PySpark. You will collaborate extensively with our larger MIS reporting team, understand the existing operational models, standardize disparate processes, and implement end-to-end automation solutions.

Key Responsibilities:

Process Analysis & Re-engineering: Conduct in-depth analysis of existing manual MIS reporting processes and data flows within USPB MIS reporting team. Identify inefficiencies, redundancies, and opportunities for standardization and automation.

Solution Design & Development: Design, architect, and develop robust, scalable, and automated data pipelines and reporting solutions. This includes ETL/ELT processes, data warehousing solutions, and reporting frameworks that meet stringent banking standards.

Technical Implementation: Implement automation solutions using advanced programming techniques with a strong focus on SAS and PySpark in a Big Data environment. Develop code, scripts, and configurations for data extraction, transformation, loading, and report generation.

Standardization & Best Practices: Drive the adoption of consistent reporting standards, data governance principles, and best practices across all MIS reporting activities. Re-engineer existing reports to ensure data quality, accuracy, and adherence to new standards.

Collaboration & Mentorship: Work closely with the MIS reporting team, business stakeholders, and IT partners to gather requirements, define technical specifications, and ensure successful delivery of automation initiatives. Provide technical leadership, guidance, and mentorship to team members.

Data Quality & Integrity: Ensure the highest levels of data quality, integrity, and security throughout the automated reporting lifecycle. Implement robust error handling, monitoring, and validation mechanisms.

Technology Advancement: Stay abreast of emerging data engineering, Big Data, and automation technologies. Propose and implement innovative solutions to continuously improve reporting efficiency and analytical capabilities.

Documentation: Create comprehensive technical documentation for all developed solutions, data models, and processes.

Required Qualifications:

Experience: 8-12 years of progressive experience in data engineering, data warehousing, business intelligence, and process automation, preferably within a large financial institution or banking environment.

Big Data Expertise: Extensive hands-on experience with Big Data technologies and ecosystems (e.g., Hadoop, Spark, Hive, Kafka).

Programming Languages: Strong proficiency in SAS programming for complex data manipulation, statistical analysis, and reporting.

Demonstrated expertise in PySpark for large-scale data processing, ETL/ELT, and automation within a Big Data context.

Database Skills: Solid understanding of relational databases (SQL Server, Oracle, etc.), SQL, data modeling (dimensional, normalized), and database performance tuning.

Automation: Proven track record of designing and implementing end-to-end data automation solutions, reducing manual efforts, and improving operational efficiency.

Analytical & Problem-Solving: Exceptional analytical, problem-solving, and critical thinking skills with the ability to translate complex business requirements into technical solutions.

Communication: Excellent verbal and written communication skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical audiences.

Collaboration: Ability to work effectively in a team-oriented, collaborative environment and influence stakeholders at various levels.

Education: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related quantitative field.

Job Family Group:

Decision Management

Job Family:

Data/Information Management

Time Type:

Full time

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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