Data Engineer

Position Overview
We are seeking a skilled and proactive Data Engineer to join our growing Data & Analytics team. This role is critical to our enterprise-wide data transformation journey, enabling scalable, secure, and high-quality data pipelines that power analytics, governance, and decision-making across the organization. The Data Engineer will work closely with Data Stewards, Architects, and Business Analysts to design, build, and optimize data flows from core banking systems and other enterprise platforms

Key Responsibilities :

Data Pipeline Development & Maintenance :

- Design, develop, and maintain robust ETL/ELT pipelines for structured and semi-structured data

- Integrate data from core systems (e.g., DNA by Fiserv), CRM, loan origination, and third-party sources

- Ensure data ingestion processes are scalable, secure, and performance-optimized

Data Lineage & Metadata Integration :

- Implement and maintain technical data lineage across pipelines and platforms to support governance, auditability, and

impact analysis

- Collaborate with Data Stewards to ensure lineage metadata is captured and surfaced in catalog tools (e.g., Collibra, Alation)

- Contribute to enterprise metadata repositories and ensure consistency across systems

Pipeline Monitoring & Issue Resolution :

- Monitor data pipelines for failures, latency, and anomalies using orchestration and observability tools (e.g., Airflow, Monte

Carlo, Datadog)

- Troubleshoot and resolve broken pipelines, ensuring timely data delivery to downstream systems and dashboards

- Maintain incident logs and root cause analyses to drive continuous improvement and reduce recurrence

Data Modeling & Architecture

- Collaborate with Data Architects and Stewards to implement dimensional and normalized models

- Translate business requirements into technical specifications and data schemas

- Support data lake and data warehouse development using cloud-native platforms

Collaboration & Governance Support :

- Work closely with Data Stewards to ensure metadata tagging, data quality enforcement, and compliance alignment

- Participate in sprint planning, code reviews, and agile ceremonies

- Document technical workflows and contribute to knowledge repositories

Qualifications :

Education & Experience :

- Bachelor's degree in Information Systems, Data Analytics, Computer Science, or related field.

- 3 years of experience in data engineering, data modelling, creating data lakes, ETL development or data platform operations roles.

- Experience in Financial services domain will be a great addition

Skills & Knowledge :

- Proficiency in SQL, Python, or Scala for data manipulation and scripting

- Experience with ETL tools (e.g., dbt, Informatica, Talend)

- Strong understanding of Oracle database architecture and query optimization

- Hands-on experience with cloud data platforms (e.g., Snowflake, BigQuery, Redshift, Databricks)

- Familiarity with version control (Git), CI/CD pipelines, and workflow orchestration

- Strong analytical skills, attention to detail, and ability to spot data anomalies.

- Excellent communication and stakeholder management skills to align technical and business teams.

Personal Attributes :

- Detail-oriented with a passion for data accuracy and quality.

- Strong sense of accountability and ownership to drive data transformation

- Collaborative mindset, able to influence stakeholders without direct authority.

- Proactive problem solver who can balance compliance with business agility.

Reporting Line :

- Reports to Head of Data and Analytics/Engineering Manager

Location & Working Model :

- Offshore supporting USA Financial services client

- Remote Working

Why Join Us?

- Be part of a growing Data & Analytics organization that treats data as a core enterprise asset.