Senior Data Engineer
Posted Updated
About the Role
We’re looking for a
Data Engineer with 4+ years of experience , with strong hands-on expertise in
data reconciliation, financial data integrity, and large-scale data validation . You’ll work closely with Product, Engineering, Finance and Operations teams to build reliable data pipelines and ensure accuracy across multiple systems.
Key Responsibilities Build and maintain
data reconciliation frameworks
across multiple systems. Develop automated checks to identify mismatches, discrepancies and missing data. Build and maintain
ETL/ELT pipelines
for large datasets. Perform transaction-level and aggregate-level reconciliation. Investigate data breaks and perform root-cause analysis. Develop SQL-based validation and data quality checks. Automate manual reconciliation processes. Work with cross-functional teams to translate business logic into scalable data solutions.
Must-Have Skills 4+ years
in Data Engineering with strong reconciliation experience. Excellent
SQL
and experience handling large datasets. Hands-on experience building reconciliation/validation frameworks. Strong understanding of
ETL/ELT, databases and data warehousing . Strong analytical and problem-solving skills. Experience troubleshooting data discrepancies and data quality issues.
Good to Have Experience in
FinTech, Banking, Payments, Lending or Investments . Experience with financial/transactional data, settlements, ledgers or payments. Exposure to
Airflow, Spark, Kafka, AWS/GCP/Azure, Snowflake or Databricks . Experience working with third-party APIs and external data sources.
Data Engineer with 4+ years of experience , with strong hands-on expertise in
data reconciliation, financial data integrity, and large-scale data validation . You’ll work closely with Product, Engineering, Finance and Operations teams to build reliable data pipelines and ensure accuracy across multiple systems.
Key Responsibilities Build and maintain
data reconciliation frameworks
across multiple systems. Develop automated checks to identify mismatches, discrepancies and missing data. Build and maintain
ETL/ELT pipelines
for large datasets. Perform transaction-level and aggregate-level reconciliation. Investigate data breaks and perform root-cause analysis. Develop SQL-based validation and data quality checks. Automate manual reconciliation processes. Work with cross-functional teams to translate business logic into scalable data solutions.
Must-Have Skills 4+ years
in Data Engineering with strong reconciliation experience. Excellent
SQL
and experience handling large datasets. Hands-on experience building reconciliation/validation frameworks. Strong understanding of
ETL/ELT, databases and data warehousing . Strong analytical and problem-solving skills. Experience troubleshooting data discrepancies and data quality issues.
Good to Have Experience in
FinTech, Banking, Payments, Lending or Investments . Experience with financial/transactional data, settlements, ledgers or payments. Exposure to
Airflow, Spark, Kafka, AWS/GCP/Azure, Snowflake or Databricks . Experience working with third-party APIs and external data sources.