ETL Developer / HPCC Data Engineer

DataSeers is looking for experienced ETL Developers / Data Engineers with HPCC Systems and ECL experience to build and maintain large-scale financial data pipelines.

A significant portion of DataSeers' data ingestion, normalization, transformation, linking, enrichment, and analytical processing is performed using HPCC Systems and Enterprise Control Language (ECL).

This is not a traditional SQL-only ETL position. You will work with large and complex financial datasets and develop ECL-based data workflows that transform disparate source data into standardized, reliable datasets used across DataSeers products.

You will work with data from banks, credit unions, fintechs, payment processors, core banking systems, and other financial platforms.

• Develop, maintain, and optimize ETL workflows using HPCC Systems and ECL.
• Build ECL datasets, records, transforms, joins, rollups, deduplication processes, and data validation logic.
• Ingest structured and semi-structured financial data from multiple sources.
• Develop data mappings from client source formats into DataSeers canonical data structures.
• Normalize inconsistent customer, account, business, signer, beneficial-owner, transaction, and counterparty data.
• Build complex entity-linking and relationship logic.
• Develop large-scale joins and matching processes across financial datasets.
• Troubleshoot incorrect joins, duplicate records, missing relationships, data-shifting issues, malformed files, and inconsistent identifiers.
• Build reusable ECL components and data-processing patterns.
• Optimize HPCC jobs for performance and scalability.
• Analyze Thor and Roxie workloads where applicable.
• Develop validation and reconciliation routines to ensure data completeness and accuracy.
• Work with MySQL, Elasticsearch, Kafka, APIs, and other components of the DataSeers ecosystem.
• Support both batch and near-real-time processing requirements.
• Work closely with customer implementation teams to understand source data and integration requirements.
• Investigate data-quality issues before they propagate into compliance, fraud, reconciliation, or reporting systems.
• Participate in code review, testing, deployment validation, and production troubleshooting.

• 3+ years of ETL, data engineering, or large-scale data-processing experience.
• Hands-on experience with HPCC Systems.
• Strong experience developing in ECL.
• Strong understanding of ECL concepts including datasets, records, transforms, joins, normalize, denormalize, rollups, deduplication, and distributed processing.
• Strong SQL skills.
• Strong understanding of data structures, relationships, and data modeling.
• Experience troubleshooting complex joins and data relationships.
• Experience working with large datasets.
• Understanding of data quality, reconciliation, referential integrity, and exception handling.
• Experience with Git or equivalent source control.
• Strong analytical and debugging skills.

• Banking, fintech, payments, or financial services experience.
• Experience working with ACH, wires, cards, RTP, FedNow, checks, or other payment data.
• HPCC Thor and Roxie experience.
• Experience optimizing large ECL jobs.
• Elasticsearch experience.
• MySQL experience.
• Kafka or event-driven processing experience.
• Experience with AML, fraud, KYC/KYB, or transaction monitoring.
• Python, JavaScript, Node.js, or Java experience is useful, but secondary to HPCC/ECL expertise.

Within the first several months, you should be able to receive a new client dataset, understand its relationships, build or modify the necessary HPCC/ECL ingestion and transformation logic, identify data-quality issues, correctly link related entities, and produce validated datasets for downstream DataSeers applications.