Data Engineer

ACCENTURE PTE LTD; Dublin; On-site; EUR 90,000 - 120,000; Full time

Job summary

ACCENTURE PTE LTD is seeking a Data Engineer to design and build scalable data pipelines and platforms using cloud technologies. You will own end-to-end data solutions from ingestion through analytics serving, collaborating with analysts, data scientists, DBAs, and architects.

The role focuses on production-grade data engineering for financial services, emphasizing data governance, performance tuning, and cost optimization.

Qualifications

• Advanced proficiency in Snowflake or Databricks with production query tuning.
• Data modeling: design normalized and dimensional schemas for analytics.
• Experience with Cloudera or Teradata on-premises platforms.
• 5+ years in data engineering roles.
• Strong SQL and Python or Scala for data transformations.

Responsibilities

• Design & build data pipelines — ETL/ELT, data transformations, real-time streaming.
• Architect data platforms — design schemas, optimize performance, ensure scalability.
• Implement data governance — access control, data quality checks, metadata tracking.
• Support banking/financial use cases — transaction data, customer analytics, risk reporting.
• Optimize performance & costs — tune queries, manage cloud resources, balance speed vs. cost.
• Collaborate with teams — work with analysts, data scientists, DBAs, and architects.
• Document & share knowledge — write runbooks, design docs, best-practice guides.

Skills

Snowflake

Databricks

SQL

Python

Scala

Data Modeling

Banking/Financial services data

Tools

Cloudera

Teradata

AWS

Azure

GCP

Job description

About the Role

We are seeking a Data Engineer to design and build scalable data pipelines and platforms using cloud technologies. You will work on enterprise data infrastructure projects across financial services, owning end-to-end data solutions from ingestion through analytics serving. This role requires strong technical depth and the ability to collaborate across teams to deliver high-quality, governed data solutions.

Key Responsibilities

• Design & build data pipelines — ETL/ELT processes, data transformations, real-time streaming
• Architect data platforms — design schemas, optimize performance, ensure scalability
• Implement data governance — manage access control, data quality checks, metadata tracking
• Support banking/financial use cases — work on transaction data, customer analytics, risk reporting
• Optimize performance & costs — tune queries, manage cloud resources, balance speed vs. cost
• Collaborate with teams — work with analysts, data scientists, DBAs, and architects
• Document & share knowledge — write runbooks, design docs, and best-practice guides

Required Qualifications

• Advanced proficiency in:Snowflake OR Databricks — production experience with complex queries, performance tuningData Modeling — design normalized/dimensional schemas for analyticsCloudera OR Teradata — experience with at least one legacy/on-premises platform
• 5+ years in data engineering roles
• Strong SQL — write efficient, optimized queries
• Python or Scala — develop data transformations and automation
• Banking or financial services data experience — familiarity with regulatory requirements (AML, reporting)

Recommended Skills

• Experience with both a cloud platform (Snowflake/Databricks) AND a traditional warehouse (Cloudera/Teradata)
• Apache Spark — distributed processing, optimization
• Data governance tools — custom metadata systems, data catalogs
• Cloud platforms — AWS, Azure, or GCP
• Real-time data — streaming pipelines, Kafka, Flink
• Agile & collaborative working environment

What We’re Looking For

• Hands-on builder — you’ve shipped multiple production pipelines
• Detail-oriented — cares about data quality, documentation, and maintainability
• Curious learner — stays current with data engineering trends
• Problem solver — debugs performance issues and proposes elegant solutions
• Team player — collaborates well, asks questions, shares knowledge