Data Analytics Engineer (Remote)

HR Talent Partner SA; United States; A distancia; USD 90.000 - 150.000; Jornada completa

Descripción de la vacante

HR Talent Partner SA seeks a Data Analytics Engineer to design and implement data warehouse solutions for reporting across finance, operations and regulatory domains. The role emphasizes building Redshift models, iterative design, and collaboration with analysts and client stakeholders in a remote setting.

You will work on data ingestion, transformation, and BI layer development using AWS Glue, Redshift, and QuickSight, with a strong emphasis on code quality, testing, and clear documentation.

Formación

• - 4+ years in data engineering, analytics engineering or another strongly SQL-based data role.
• - Advanced SQL: modular and layered model design, window functions, complex joins and aggregations, and query performance tuning.
• - Hands-on cloud data warehouse experience, ideally Redshift. Strong Snowflake, BigQuery or Synapse experience will be considered, provided you understand distribution and sort key style optimisation or its equivalent
• - Python for ETL and data transformation work, whether in Glue, PySpark, pandas or a comparable setting
• - Practical experience with AWS data services such as Redshift, Glue, S3 and DMS
• - Experience building or supporting a BI layer in QuickSight, Power BI, Tableau or Looker
• - Comfortable working in Git, raising pull requests and reviewing other people’s SQL
• - A track record of turning ambiguous or evolving reporting requirements into defined, documented logic
• - An accuracy mindset. You reconcile, you check your numbers, and you can explain exactly how a figure was derived
• - Clear written and spoken English, and confidence working directly with client teams across time zones

Responsabilidades

• Design and build layered Redshift SQL views and models for reporting across financial activity, accounts receivable ageing and operational health
• Build analytics and calculation views that compute regulated healthcare reporting values, and map source clinical and operational data to prescribed national dataset specifications
• Develop and maintain Python ETL jobs in AWS Glue for ingestion and transformation
• Support replication and migration of source data into the warehouse using AWS DMS and Zero-ETL integrations
• Share and query data across accounts and the data lake using Redshift datashares and Redshift Spectrum
• Build and maintain QuickSight datasets and dashboards on top of the reporting layer
• Translate reporting requirements into agreed metric definitions and documented calculation logic with analysts and client stakeholders
• Reconcile outputs against source systems and prior reporting, and investigate variances through to a clear explanation
• Build data quality checks, testing and documentation into delivery as standard, not as an afterthought
• Manage data infrastructure as code using Terraform where relevant

Conocimientos

SQL

Python

AWS Redshift

Snowflake

BigQuery

QuickSight

Power BI

Tableau

Looker

Git

Herramientas

AWS Glue

DMS

Zero-ETL integrations

Terraform

Descripción del empleo

Data Analytics Engineer (Remote) job vacancy in South Africa.

A well establish international software development company is looking for a Data Analytics Engineer to join their team in either Somerset West, Pretoria or Johannesburg.

This is a fully remote position, with the option to work from the office once a week if you prefer a hybrid working arrangement. You also have the option of choosing between permanent or contract employment, with a requirement to work 8 normal working hours per day.

Overview:

The work is primarily data warehousing and reporting, with ingestion and migration alongside it. You will spend most of your time building the Redshift models and views that power financial, operational and regulatory reporting, and turning reporting requirements into calculation logic that holds up under scrutiny.

This is a build role rather than a maintenance one.

The reporting layer is being established now, so you will help shape how models are structured, documented and tested rather than inheriting a finished platform.

You will work closely with analysts, delivery leads and client stakeholders, so being able to ask the right questions early matters as much as the SQL.

Requirements:

• 4+ years in data engineering, analytics engineering or another strongly SQL-based data role
• Advanced SQL: modular and layered model design, window functions, complex joins and aggregations, and query performance tuning
• Hands-on cloud data warehouse experience, ideally Redshift. Strong Snowflake, BigQuery or Synapse experience will be considered, provided you understand distribution and sort key style optimisation or its equivalent
• Python for ETL and data transformation work, whether in Glue, PySpark, pandas or a comparable setting
• Practical experience with AWS data services such as Redshift, Glue, S3 and DMS
• Experience building or supporting a BI layer in QuickSight, Power BI, Tableau or Looker
• Comfortable working in Git, raising pull requests and reviewing other people’s SQL
• A track record of turning ambiguous or evolving reporting requirements into defined, documented logic
• An accuracy mindset. You reconcile, you check your numbers, and you can explain exactly how a figure was derived
• Clear written and spoken English, and confidence working directly with client teams across time zones

The Stack You Will Work In:

• Warehouse: Amazon Redshift, including datashares and Redshift Spectrum
• Ingestion and transformation: AWS Glue (Python), AWS DMS, Zero-ETL integrations
• Reporting and BI: Amazon QuickSight
• Languages: SQL (Redshift), Python, some Terraform
• Ways of working: Git-based workflow with version-controlled SQL, peer review, agile delivery

Nice To Have:

• Redshift datashares, Spectrum or Zero-ETL integrations used in production
• Terraform or another infrastructure as code tool applied to data infrastructure dbt or a comparable transformation and testing framework
• Regulated or standards-driven reporting experience in healthcare, financial services or the public sector, where definitions are prescribed and outputs are auditable
• Financial reporting domain knowledge such as accounts receivable ageing, revenue or activity reporting
• Orchestration tooling such as AWS Step Functions, Airflow or MWAA
• Data quality, observability or data testing frameworks

Duties and Responsibilities:

• Design and build layered Redshift SQL views and models for reporting across financial activity, accounts receivable ageing and operational health
• Build analytics and calculation views that compute regulated healthcare reporting values, and map source clinical and operational data to prescribed national dataset specifications
• Develop and maintain Python ETL jobs in AWS Glue for ingestion and transformation
• Support replication and migration of source data into the warehouse using AWS DMS and Zero-ETL integrations
• Share and query data across accounts and the data lake using Redshift datashares and Redshift Spectrum
• Build and maintain QuickSight datasets and dashboards on top of the reporting layer
• Translate reporting requirements into agreed metric definitions and documented calculation logic with analysts and client stakeholders
• Reconcile outputs against source systems and prior reporting, and investigate variances through to a clear explanation
• Build data quality checks, testing and documentation into delivery as standard, not as an afterthought
• Manage data infrastructure as code using Terraform where relevant