Key Responsibilities

Pipeline & Architecture Design, build, and maintain scalable, real-time, and batch data pipelines.

Data Strategy Help execute data strategy, architecture, and best practices across the organization.

Platform Management Develop new requirements across multiple platforms, including Enterprise Data Lakes (on-premises), Azure Data Lake, Business Intelligence, Advanced Analytics, and Real-time Streaming platforms.

End-to-End Delivery Estimate project efforts, design effective solutions, and handle change release and resource management.

Domain Integration Work closely with data-intensive systems across banking lines of business, digital journeys, marketing, risk, and compliance across operating regions (UAE, Egypt, Pakistan, etc.).

Critical Reporting Handle critical applications that influence the bank’s management decision-making processes, operational reporting, and regulatory reporting (which impacts financial/non-financial compliance).

Mentorship & Leadership Lead team deliverables across business groups and drive the organization toward making strategic improvements in data engineering.

Requirements & Qualifications

Experience 6 to 8 years of experience in Data Engineering, Big Data,



or DWH/ETL roles (years of experience vary slightly depending on the specific internal band, such as AVP vs. Lead).

Banking Knowledge Solid functional knowledge of financial services, core banking systems, retail / corporate banking, risk, and compliance.

Data Modeling Experience in designing and building dimensional data models to improve the accessibility, efficiency, and quality of data.

Software Lifecycle Strong understanding of Agile methodologies, CI/CD processes, and managing production go-live engagements.

Technical Skills & Tech Stack

Programming Languages Python, Scala, Advanced SQL/PL-SQL (Expertise in performance tuning SQLs).

Big Data Ecosystem Hadoop, Apache Spark, PySpark, Hive, Hue, Sqoop, MapReduce.

Cloud Infrastructure Microsoft Azure (Azure Data Lake Storage, Azure Data Factory, Azure Synapse, Azure Databricks).

Real-time Streaming Apache Kafka, Spark-Streaming, Storm.

Databases Strong knowledge of NoSQL data modeling and Relational SQL databases (PostgreSQL, Cassandra, Couchbase, Oracle).

Other Tools Airflow, Databricks, ELT/ETL pipelines, MicroStrategy/Power BI (for downstream BI).

📌 Consultant (Hyderabad)
🏢 Virtusa
📍 Hyderabad