Lead Data Engineer (Banking)
Unison Group Open · verified Oct 24, 2026 At a glance
Senior Data Engineering role at Unison Group. Singapore · full-time.
Pay not stated Lead Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and deliver production data pipelines for banking customer, account, transaction, payments and AML information
- Process historical data through snapshots and backfills, checking control totals and producing validation reports
- Develop ETL/ELT and change-data-capture flows, including metadata-led automation and parameterized SQL
- Monitor reconciliation, data quality and service levels while tuning Teradata queries for large, multi-year datasets
- Set engineering frameworks and code practices, review work, estimate delivery and guide engineers alongside architects and analysts
What you bring
- Lead-level experience requires at least twelve years in data engineering, including six in banking
- You have delivered bank data pipelines in production and worked within bank release, scheduling and change controls
- Hands-on capability with Teradata SQL, BTEQ, TPT and FastLoad or MultiLoad, plus query tuning
- Experience with Spark and the listed data platforms, integration tools and workflow systems
Who this fits
This is an onsite role in Singapore for a senior banking data engineer. The lead remit includes guiding engineers and setting standards, alongside hands-on pipeline and platform work.
From the employer
Role: Lead Data Engineer (Banking)
Must-have skills
Banking and domain
• Production delivery of data pipelines inside banks.
• Customer, account, transaction, payments and AML data.
• Working within bank release, scheduling and change controls.
Core data engineering
• Teradata SQL, BTEQ, TPT and FastLoad/MultiLoad; query tuning.
• Spark (PySpark/Scala), Hive, Impala, HBase, Pig and Hue; Apache Iceberg and Trino; Python and R.
• Historical data processing: snapshots, SCD Type 2 and multi-grain backfills with control totals and validation reports.
• ETL/ELT development, CDC, metadata-driven automation frameworks and parameter-driven SQL generation.
• Reconciliation, data quality and SLA monitoring.
• Performance at scale: tables of 1 billion+ rows and multi-year history.
Requirements
Experience:
- Lead: 12+ years, including 6+ in banking.
- Senior: 8+ years, including 4+ in banking ·
Banking and domain
• Production delivery of data pipelines inside banks.
• Customer, account, transaction, payments and AML data.
• Working within bank release, scheduling and change controls.
Core data engineering
• Teradata SQL, BTEQ, TPT and FastLoad/MultiLoad; query tuning.
• Spark (PySpark/Scala), Hive, Impala, HBase, Pig and Hue; Apache Iceberg and Trino; Python and R.
• Historical data processing: snapshots, SCD Type 2 and multi-grain backfills with control totals and validation reports.
• ETL/ELT development, CDC, metadata-driven automation frameworks and parameter-driven SQL generation.
• Reconciliation, data quality and SLA monitoring.
• Performance at scale: tables of 1 billion+ rows and multi-year history.
Integration and platforms
• Kafka, Spark Streaming, Informatica (PowerCenter, IDMC, IDL) and Talend; REST API development.
• Denodo, Snowflake and NoSQL databases.
• Airflow, Control-M or Autosys; Git, CI/CD, GitOps and Kubernetes.
Delivery and communication (Lead)
• Framework design, code standards, code reviews and estimation.
• Guiding a team of engineers and working with architects and analysts.
Good-to-have skills
• Databricks: Delta Lake, Unity Catalog and Workflows.
• Data services on Azure, Google Cloud, Huawei Cloud or Alibaba Cloud.
• Data modelling for Qlik Sense or Power BI.
Certifications (preferred): Teradata Vantage; Cloudera Data Engineer; Databricks Data Engineer Associate or Professional
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