Data Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Assist in enhancing and supporting data engineering solutions that facilitate Financial Crime Risk and/or Legal and Corporate Technology platforms.

• Design, develop, and uphold scalable and resilient data ingestion, transformation, and reconciliation pipelines.

• Integrate data from various internal and external sources into current platforms and data repositories.

• Transform and refine raw data to conform to target business and technical data models.

• Migrate and modernize existing data pipelines as enterprise frameworks, tools, and standards evolve.

• Develop and optimize intricate SQL transformations and large-scale distributed data processing tasks.

• Implement data quality controls, validation frameworks, reconciliation processes, and monitoring functions.

• Conduct root cause analysis and troubleshoot data and platform challenges across development, testing, and production environments.

• Engage in production support, operational incident management, and participate in on-call support rotations.

• Enhance platform reliability, observability, and operational processes through automation and engineering best practices.

• Collaborate with data architects, platform engineers, business stakeholders, and delivery teams.

• Contribute to source control, CI/CD pipelines, automated testing, and release management.

• Foster engineering excellence through knowledge sharing, continuous improvement, and technical leadership.

⛳️ Requirements

• Extensive hands-on experience in developing enterprise-scale data engineering solutions.

• Proficient in advanced SQL development with a strong background in processing and analyzing large datasets.

• Strong Python development capabilities for data processing, automation, and integration tasks.

• Experience in building and maintaining complex ETL and ELT pipelines.

• Solid understanding of data integration patterns and multi-source data processing methodologies.

• Familiarity with structured, semi-structured, and large-volume datasets.

• Comprehensive understanding of data modeling principles and data access strategies.

• Experience with AWS services, particularly Amazon S3, Amazon RDS, EKS, EC2, Lambda, and IAM.

• Background in developing and supporting cloud-based data platforms.

• Experience with source control systems and contemporary software development practices.

• Strong expertise in implementing data quality controls and validation frameworks.

• Experience in designing reconciliation processes, control totals, and load assurance mechanisms.

• Proven experience in troubleshooting production issues and supporting critical business systems.

• Experience participating in operational support and incident management workflows.

• Familiarity with CI/CD pipelines and automated deployment practices.

• Experience with Agile delivery methodologies.

• Strong communication and stakeholder engagement skills.

• Ability to balance delivery outcomes with operational stability and platform resilience.

• Experience with Apache Spark or distributed data processing frameworks.

• Familiarity with orchestration technologies such as Apache Airflow, Argo Workflows, Control-M, or similar.

• Experience with AWS Glue.

• Proficiency in using Trino or Presto.

• Experience with containerized workloads and Kubernetes platforms, preferably AWS EKS.

• Background in modernizing or migrating enterprise data pipelines to new ingestion, orchestration, or cloud-based platforms.

• Familiarity with OpenSearch / Elasticsearch platforms.

• Experience working within banking, financial services, or regulated environments.

• Exposure to technologies and business processes related to Financial Crime Risk.

• Familiarity with Actimize, ActOne, Quantexa, or similar financial crime platforms.

🏝️ Benefits

• Government-mandated benefits along with supplemental HMO coverage.

• A collaborative and professional work environment.

• Opportunities for career growth within an expanding technology organization.

• Hybrid/Remote work arrangements (where applicable).

• Training and support to facilitate career advancement.