Data Engineer

Accenture Pte Ltd; Região Norte; On-site; BRL 180,000 - 320,000; 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 across teams to deliver governed data solutions.

Responsibilities include architecture design, data governance, and optimizing performance and costs for banking/financial use cases, with a strong emphasis on SQL, Python/Scala, and cloud data platforms.

Qualifications

• 5+ years of data engineering experience.
• Advanced proficiency in Snowflake or Databricks with performance tuning.
• Data modeling expertise (normalized and dimensional schemas) for analytics.
• Experience with Cloudera or Teradata (on‑premises/legacy).
• Strong SQL and Python or Scala skills.

Responsibilities

• Design and build scalable data pipelines (ETL/ELT) and real-time streaming.
• Architect data platforms and optimize for performance and cost.
• Implement data governance, data quality checks, and metadata tracking.
• Support banking and financial services data use cases (AML, reporting).
• Collaborate with analysts, data scientists, DBAs, and architects; document runbooks and design guides.

Skills

Strong SQL

Python or Scala

Banking/financial services data

5+ years experience

Tools

Snowflake

Databricks

Cloudera

Teradata

Apache Spark

Kafka

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