Sr Data Engineer Banking Domain - BigTapp Pte Ltd

Job Title: Sr Data Engineer Banking Domain

Location: Chennai (Dubai Onsite)

Experience: 5 years

Must Skills: SQL, ETL Pipelines, DWH, Hadoop & AWS/Azure

Job Reference ID: BT/F55/IND

Job Summary:

The Senior Data Engineer specializing in the Banking Domain is responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support the data needs of banking operations. The Senior Data Engineer is responsible for leading a team of data engineers and ensuring the successful execution of ETL processes to support business intelligence and data analytics initiatives. The role will involve understanding core analytics competencies across the full spectrum of analytics including data integration, data modeling, and dashboard creation.

Responsibilities:

1. Data Pipeline Development:
   Design, develop, and maintain robust data pipelines to ingest, transform, and load data from various sources including transactional systems, data warehouses, and external APIs. Implement ETL (Extract Transform Load) processes to clean, enrich, and harmonize data for analysis and reporting purposes. Optimize data pipelines for performance, scalability, and reliability leveraging technologies such as Apache Spark, Kafka, and Airflow.
2. Data Modeling and Architecture:
   Design and implement data models and schemas that reflect the business requirements and support efficient data storage, retrieval, and analysis. Define data architecture standards and best practices and ensure compliance with data governance policies and regulatory requirements. Collaborate with data architects and solution architects to design end-to-end data solutions that align with business objectives and technical constraints.
3. Data Quality Assurance:
   Develop and implement data quality checks, validation rules, and monitoring mechanisms to ensure the accuracy, completeness, and consistency of banking data. Identify and address data quality issues and anomalies working closely with data stewards, business users, and IT teams to resolve data discrepancies. Establish data quality metrics and KPIs to measure and report on data quality levels and implement continuous improvement initiatives to enhance data quality over time.
4. Collaboration and Leadership:
   Collaborate with cross-functional teams including data scientists, business analysts, and software engineers to deliver integrated data solutions that meet business requirements. Mentor and coach junior data engineers providing guidance on technical best practices, industry trends, and professional development opportunities. Stay abreast of emerging technologies and tools in the data engineering field and evaluate their potential for adoption within the organization.

Requirements:

Excellent communication skills with the ability to collaborate effectively with cross-functional teams and communicate technical concepts to non-technical stakeholders. Strong problem-solving skills and the ability to troubleshoot complex issues in a fast-paced environment.

Qualifications:

• Bachelor's degree in computer science, Information Systems, or related field. Master's degree preferred.
• 5 years of experience in data engineering with a focus on the banking domain.
• Strong proficiency in SQL, Python, and ETL tools for data integration and manipulation.
• Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure) for scalable data processing and storage.
• Solid understanding of data modeling techniques, data warehousing concepts, and database management systems.
• Excellent problem-solving, analytical, and communication skills.
• Certification in relevant technologies (e.g., AWS Certified Big Data Specialty, Cloudera Certified Professional) is a plus.

Why Join Us:

• Opportunities for professional growth and development.
• Collaborative and innovative work environment.
• Exposure to the latest technologies and industry trends.

Salary: Commensurate with experience and demonstrated competence

Contact: confidential