Project description

Engineer responsible for developing ingestion and transformation pipelines to populate the reconciliation staging area and support downstream integration with FIS Matching.

Responsibilities
Solid hands‑on experience as a Senior Data Engineer in cloud environments, primarily AWS.
Solid proficiency with SQL and relational and analytical database platforms.
Proven experience designing and building ETL / ELT data pipelines
Experience integrating legacy systems with modern SaaS or cloud‑based platforms
Practical experience with cloud data warehouses or lake‑style platforms (e.g. Snowflake or equivalent)
Working knowledge of data lake / lakehouse concepts
Experience with job scheduling and pipeline orchestration tools (e.g. Airflow, Step Functions or similar)
Experience implementing data security, encryption, privacy controls and governance practices
Strong software engineering discipline, including GitHub usage (branching, pull requests, code reviews)





Skills

Must have
5+ years of experience.
AWS / ETL / Redshift / SnowFlake
Iceberg tables & data lakehouse concepts
Catalog/schema management
Job scheduling / pipeline orchestration tools
Data encryption, privacy, governance frameworks
GitHub usage (branches, PRs, code review).
Knowledge of Kinesis, Aurora, Athena,DMS, DataSync

Nice to have
Familiarity with Apache Iceberg or similar up-to-date table formats
Exposure to data catalogue and schema management tooling
Awareness of AWS data services such as Kinesis, Aurora, Athena, DMS and DataSync
Experience working in environments where technology choices are evolving, rather than fixed
Broader awareness of up-to-date data platform architectures, even where tools are not used day to day
J-18808-Ljbffr

📌 Senior Data Engineer Melbourne
🏢 Luxoft
📍 Melbourne