Senior Data Engineer

Please note: Our client is unable to provide visa sponsorship for this role now or in the future. Candidates must already be authorized to work in the United States without current or future sponsorship.
Senior Data Engineer
Employment Type: Full time
About the Role
We are working with a growing financial technology company looking for a Senior Data Engineer to take ownership of the data infrastructure supporting its banking and payments products.
The company has already established the foundation of its AWS data platform, including a lakehouse architecture, ingestion framework, financial data model, and initial reporting datasets. The next step is turning that foundation into a reliable production data platform that can scale as the business adds new banking partners, card processors, and financial products.
This is a highly hands on Data Engineering role focused on financial and transactional data. You will work with complex datasets across processors, sponsor banks, internal systems, and external partners, while building reliable pipelines and ensuring financial activity can be accurately reconciled across systems.
This is not primarily a BI or dashboard focused position. The ideal candidate enjoys building data infrastructure, tracing transactions across systems, investigating discrepancies, and making financial data trustworthy and production ready.
What You’ll Do
Take ownership of an existing AWS lakehouse platform and move it from development into production
Build, improve, and maintain reliable ETL and ELT pipelines
Build and maintain Bronze, Silver, and Gold data layers
Expand financial data models across multiple processors, banks, and internal systems
Build automated data quality testing, monitoring, alerting, and observability
Manage historical backfills and incremental data processing
Ingest data from APIs, relational databases, SFTP files, and other external systems
Normalize financial data from different banking and processing partners into consistent internal models
Build reconciliation pipelines across processors, sponsor banks, internal systems, and ledger data
Investigate missing transactions, balance discrepancies, duplicate activity, settlement differences, and other financial data exceptions
Support upcoming bank and card processor migrations
Map legacy financial data into new processor and banking structures
Preserve historical transaction and account data during migrations
Validate balances and financial activity before and after migration cutovers
Build reliable datasets for Finance, Operations, Risk, Product, and Engineering
Improve pipeline reliability, performance, monitoring, recovery, and documentation
What We’re Looking For
Strong hands on experience with Data Engineering, SQL, AWS, and data modeling is essential.
You should be comfortable owning production data pipelines and working with large, complex transactional datasets where data accuracy matters.
Ideal experience includes:
AWS
SQL
ETL and ELT pipelines
Data modeling
Lakehouse or modern data warehouse architectures
APIs
Relational databases
SFTP and flat file ingestion
Incremental processing
Historical backfills
Data quality testing
Pipeline monitoring and observability
Large transactional datasets
Canonical or normalized data models
Financial reconciliation
Experience with reporting platforms such as QuickSight, Metabase, Looker, Tableau, or similar tools is also valuable.
Experience working with payments, fintech, banking, or other financial transaction data is strongly preferred.
Particularly relevant experience includes:
Card issuing or card processing
Payment transactions
Authorization, clearing, and settlement
ACH and bank transaction data
Financial reconciliation
Ledgers and balance calculations
Sponsor bank integrations
Payment processor integrations
Visa or Mastercard network data
Processor or bank migrations
Historical financial data migrations
This is a great opportunity for a Data Engineer who enjoys taking ownership of complex data infrastructure, working with financial transaction data, solving reconciliation problems, and helping build a scalable data platform that supports evolving banking and payments infrastructure.

Work arrangement
No