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Project Description:
As part of Client Technology team, the data Engineer will work to design, develop, and support scalable data solutions that underpin strong engineering practices, implicit data controls and the functional requirements for effective surveillance and regulatory reporting use cases. The scope will focus on onboarding new data sources, developing data ingestion and transformation pipelines, implementing data quality controls, supporting lineage and metadata requirements, and enabling efficient management of transactional and non-transactional/ reference data across the platform. The role will support both strategic initiatives and ongoing operational requirements.
Responsibilities:
• Onboarding and integration of new surveillance and transaction data sources.
• Development and maintenance of data pipelines and ingestion frameworks.
• Implementation of data quality rules, monitoring, and exception management processes.
• Optimization of data processing performance and platform scalability.
• Support for data lineage, metadata management, and governance objectives.
• Resolution of data-related production issues and operational support activities.
• Delivery of technical documentation and adherence to SDLC and control standards.
Mandatory Skills Description:
Education:
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
Experience:
- Minimum of 8 years of experience in data engineering, with a strong focus on SQL and data manipulation.
- Proven experience working with Snowflake or other cloud-based data warehousing solutions.
- Experience with Tableau
- Strong background in designing data model and building scalable data pipelines and data models.
- Solid understanding of financial instruments, investment operations, investment reporting and portfolio management concepts.
- Knowledge of investment performance measurement, risk analysis, and portfolio management concepts.
Skills:
- Expert-level proficiency in SQL, with the ability to write complex queries and optimize them for performance.
- Strong experience with ETL tools and processes.
- Familiarity with Tableau, Qlikview, Qliksense
- Familiarity with programming languages such as Python.
- Knowledge of data governance, security, and compliance best practices.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills.
Nice-to-Have Skills Description:
Banking Domain
Languages:
English: C2 Proficient
Job ID: 151835169
Skills:
snowflake , Data Warehousing, Kafka, ELT, Kinesis, Terraform, Python, Data Security, Apache Spark, Sql, Databricks, Aws S3, Etl, Airflow, cdc, incremental loads, data quality frameworks, Great Expectations, Prefect, data cataloging, ML feature pipelines, dbt, lineage tools, Databricks Jobs
Skills:
Apache Airflow, Azure Data Factory, Databricks, Python, Sql
Skills:
Powershell Scripting, Sql, Azure Synapse, Git, Azure Data Factory, Azure Data Lake, Databricks, Sap Odata, Etl, Azure Blob, Agile Software Development methodologies, Azure Storage Explorer, Data Factory pipelines, streaming technologies, SQL stored procedures
Skills:
containerization , Aws Services, Gcp, Azure, Python, alerting systems, data pipelines, cloud platforms, model registry, data ingestion, feature store, MLOps architecture, DevOps principles
Skills:
snowflake , Metadata Management, Power Bi, Sql, ELT, Data Quality, Data Governance, Python, AWS, Informatica IICS, Matillion, CI CD, dbt, Fivetran