31 Oct
|
ALP (Computational Finance, AI and Data Engineering)
|
Bengaluru
31 Oct
ALP (Computational Finance, AI and Data Engineering)
Bengaluru
– Junior Data Engineer
Experience: 2–4 years
Type: Full-time
Location: Bengaluru, with frequent GCC travel
About ALP
Angel Lane Partners (ALP) is a computational finance, data engineering and AI/ML firm with offices in Dubai, London, Bengaluru and Riyadh. We work with banks, financial institutions and government entities across the GCC.
Role Overview
You will build and maintain the data pipelines behind the analytics and calculation platforms ALP delivers to financial-services clients. Working with senior data engineers, backend developers and analysts, you will develop ingestion jobs, data-quality checks and data models that feed calculations and reports. You will write production SQL and Python, test your own pipelines, and support them in client environments.
Travel The role is based in Bengaluru, with frequent travel to client sites in the GCC, sometimes for several weeks at a time. A valid passport is required.
Key Responsibilities
- Build and maintain ETL/ELT pipelines in Python, SQL and ETL tools such as Informatica or SSIS, pulling data from databases, APIs, views and file/folder feeds, following designs set by senior engineers.
- Develop and schedule workflows in Airflow or Prefect, including retries, task dependencies, backfills and failure alerts.
- Implement controlled file ingestion steps (detect → archive → validate → accept/reject → load → notify), with full-file rejection and exception reports.
- Write data-quality checks covering mandatory fields, data types, allowed values and ranges, duplicates, referential integrity, and source-to-target reconciliation.
- Build full and incremental loads with batch IDs, checksums and watermarks, so pipelines can be rerun without duplicating or losing data.
- Load and transform data across the Landing/Raw → Staging → Core → Data Mart layers, including SCD2 tables and effective-dated reference data.
- Write and tune SQL for transformations, and work with senior engineers on indexing and execution-plan reviews.
- Write unit,
integration and reconciliation tests for your pipelines.
- Record lineage, metadata and audit-trail information for the data you load.
- Monitor scheduled jobs, investigate failures, and document root causes and fixes.
- Work with analysts and client data owners on source-to-target mapping, as-of dates and cut-off logic.
- Follow access-control, masking and retention rules on client data, and keep pipeline documentation current.
Required Skills
- 2–4 years in data engineering, or in a development or analytics role with substantial pipeline work.
- Strong SQL, including joins, window functions, CTEs, aggregations and reading execution plans.
- Hands-on PostgreSQL or Microsoft SQL Server, including stored procedures, transactions and basic indexing.
- Python for ETL (pandas, SQLAlchemy, database connectors).
- Experience building and running data pipelines in production with Python, Informatica, SSIS or similar ETL tools.
- Hands-on AWS experience, such as S3, RDS, Glue or Lambda.
- Experience with Airflow, Prefect or a comparable scheduler/orchestrator.
- Loading data from diverse sources: databases, APIs, flat files and spreadsheets.
- Understanding of data modelling concepts: 3NF, fact and dimension tables, star schema, SCD2, effective dating.
- Git, including branching and pull-request reviews.
- Writing automated tests for data code.
Preferred Skills
- Exposure to banking or financial-services data (transactions, exposures, positions, market rates) and related concepts such as business dates, cut-offs, control totals and reconciliation.
- Teradata or Oracle.
- PySpark or Databricks; columnar file formats such as Parquet.
- Azure; Docker.
- Certifications in BI, ML, cloud or infrastructure.
- dbt or a similar SQL transformation framework.
- CI/CD for pipeline and database changes.
- Logging and monitoring tools (e.g. Grafana).
- Preparing datasets for BI tools such as Power BI, or for quant models.
Qualifications
- Bachelor's or master's degree in Computer Science, Data Engineering, IT or a related field.
- Able to explain data issues clearly to analysts and client teams, in writing and in person.
📌 Junior Data Engineer (Bengaluru)
🏢 ALP (Computational Finance, AI and Data Engineering)
📍 Bengaluru