Mid / Senior Data Engineer or Analyst (Citizens with Baseline)

XPT Software; Sydney; On-site; AUD 110,000 - 170,000; Full time

Job summary

XPT Software Australia Pty Ltd is seeking a Mid to Senior Data Engineer or Analyst (Citizens with Baseline) to join our data team. You will build and maintain data pipelines, profile, cleanse, transform and migrate data for client projects, ensuring version control and reproducibility.

The role reports to the Data Architect and emphasizes data quality, reconciliation, and providing masked test data for non-production environments.

Qualifications

• Data engineering on a modern platform.
• SQL and Python or Spark; data quality and reconciliation.
• Desirable: Databricks; mainframe or Informix data extraction; registry or financial data.

Responsibilities

• Build version controlled pipelines for profiling, cleansing, transformation and migration.
• Automate reconciliation between legacy and target (counts, control totals, field comparisons).
• Provide masked test data for non production environments.
• Document pipelines and pair with ASIC data staff.

Skills

SQL

Python

Spark

Tools

Databricks

Mainframe

Informix

Job description

Mid / Senior Data Engineer or Analyst (Citizens with Baseline)

• XPT SoftwareAustralia PTY Ltd, incorporated in 2016, is a Software Services company
• XPT works with topclients across Australia in Banking, Insurance, Telecom,Retail, Energy, Mining and Manufacturingdomains.
• We have 120+technocrats in Australia working at our clientlocations.
• XPT SoftwareAustralia is part of group companies which has globalpresence across India & Europe.
• We have served100+ clients globally, fulfilling their onsite-offshoreneeds.

Purpose: provide data engineering and analysis skillsto data heavy deliverables.

Seniority: Mid to senior.

Reports to: DataArchitect.

Responsibilities

• Build version controlled pipelines for profiling,cleansing, transformation and migration.
• Automate reconciliation between legacy and target(counts, control totals, field comparisons).
• Provide masked test data for non productionenvironments.
• Document pipelines and pair with ASIC data staff.

Essential: data engineering on a modern platform; SQLand Python or Spark; data quality and reconciliation.

Desirable: Databricks; mainframe or Informix data extraction; registry or financial data.