Lead Data Engineer

2 weeks ago

Dallas, TX, United States Anblicks Full time
Data Engineering Manager (BFSI Domain)

Summary: We are seeking an experienced and strategic Data Engineering Manager to lead our data platform team. This role is critical in designing, building, and maintaining scalable, secure, and compliant data pipelines and infrastructure that power analytics, reporting, and regulatory requirements across the BFSI domain. The Manager will be responsible for technical roadmaps, team mentorship, and ensuring data integrity and governance.

Key Responsibilities:

Technical Leadership & Architecture: Define the technical roadmap and architecture for the data platform (Data Lake, Data Warehouse, ETL/ELT pipelines), optimizing for performance, security, and high availability.

Team Management & Mentorship: Lead, mentor, and manage a team of data engineers, fostering a culture of technical excellence, accountability, and continuous improvement.

Pipeline Development & Operations: Oversee the design, construction, and deployment of robust, production-grade data pipelines (batch and real-time) to ingest, transform, and serve large volumes of financial data.

Data Governance & Compliance (BFSI Focus): Collaborate closely with Compliance, Risk, and Security teams to implement and enforce strict data governance standards, regulatory reporting requirements (e.g., Basel, KYC), and robust data masking/security controls.

Cloud Strategy: Drive the effective utilization of cloud-native data services (e.g., Snowflake, Databricks, Azure Synapse, AWS Redshift) to scale data processing capabilities.

Quality & Integrity: Establish automated testing frameworks and validation processes to ensure the accuracy, completeness, and auditability of all data assets.

Required Skills & Experience:

Minimum of 8 years of experience in Data Engineering, with at least 3 years in a management or technical leadership role.

Domain Expertise (BFSI Mandatory): Deep understanding of financial data models, transactional systems, and the regulatory environment governing data management (e.g., data residency, audit trails, secure data handling).

Cloud Proficiency: Expert knowledge of cloud-native data services (Azure, AWS, or GCP), including expertise in Snowflake, Databricks, or similar modern data stack technologies.

Advanced Programming: Expert proficiency in SQL and programming languages such as Python (for ETL scripting) or Scala.

Data Orchestration & Modeling: Extensive experience with modern data orchestration tools (e.g., Apache Airflow, Azure Data Factory) and dimensional/data vault modeling.

Strong communication skills with the ability to translate complex technical concepts into business terms for executive stakeholders.

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