Data Engineer at Accenture

Manila, Metro Manila, Philippines

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Data EngineeringIndustries

Requirements

Excellent programming and debugging skills in Python
Strong hands-on experience with PySpark to build efficient data transformation and validation logic
Proficient in at least one cloud platform: AWS, GCP, or Azure
Experience with cloud-based services relevant to data engineering, data storage, data processing, data warehousing, real-time streaming, and serverless computing
Hands-on experience in applying performance optimization techniques
Understanding of data modeling and data warehousing principles
Minimum 2 years of experience

Responsibilities

Develop high-quality, scalable ETL/ELT pipelines using Databricks technologies including Delta Lake, Auto Loader, and DLT
Create modular dbx functions for transformation, PII masking, and validation logic — reusable across DLT and notebook pipelines
Implement ingestion patterns using Auto Loader with checkpointing and schema evolution for structured and semi-structured data
Build secure and observable DLT pipelines with DLT Expectations, supporting Bronze/Silver/Gold medallion layering
Configure Unity Catalog: set up catalogs, schemas, user/group access, enable audit logging, and define masking for PII fields
Enable secure data access across domains and workspaces via Unity Catalog External Locations, Volumes, and lineage tracking
Access and utilize data assets from the Databricks Marketplace to support enrichment, model training, or benchmarking
Collaborate with data sharing stakeholders to implement Delta Sharing — both internally and externally
Integrate Power BI/Tableau/Looker with Databricks using optimized connectors (ODBC/JDBC) and Unity Catalog security controls
Build stakeholder-facing SQL Dashboards within Databricks to monitor KPIs, data pipeline health, and operational SLAs
Prepare GenAI-compatible datasets: manage vector embeddings, index with Databricks Vector Search, and use Feature Store with MLflow
Package and deploy pipelines using Databricks Asset Bundles through CI/CD pipelines in GitHub or GitLab
Troubleshoot, tune, and optimize jobs using Photon engine and serverless compute, ensuring cost efficiency and SLA reliability

Skills

Key technologies and capabilities for this role

DatabricksDelta LakeAuto LoaderDLTPythonPySparkAWSGCPAzureUnity CatalogETLELTSQLPower BITableauLookerCI/CDMLflowVector Search

Questions & Answers

Common questions about this position

What are the key required skills for this Data Engineer role?

The role requires excellent programming and debugging skills in Python, strong hands-on experience with PySpark for data transformation and validation, and proficiency in at least one cloud platform: AWS, GCP, or Azure. Additional essentials include experience with Databricks technologies like Delta Lake, Auto Loader, DLT, and Unity Catalog, plus understanding of data modeling and data warehousing principles.

What is the minimum experience required for this position?

Minimum 2 years of experience is required for this Data Engineer role.

What salary or compensation does this role offer?

This information is not specified in the job description.

Is this Data Engineer position remote or does it require office work?

This information is not specified in the job description.

What 'good to have' skills or certifications would make my application stronger?

Good to have skills include Databricks Certified Professional or similar certifications, knowledge of machine learning concepts, big data processing like Spark or Kafka, Apache Airflow, CI/CD pipelines, ETL tools like Informatica or dbt.

Accenture

Global professional services for digital transformation

About Accenture

Accenture provides a wide range of professional services, including strategy and consulting, technology, and operations, to help organizations improve their performance. Their services assist clients in navigating digital transformation, enhancing operational efficiency, and achieving sustainable growth. Accenture's offerings include cloud migration, cybersecurity, artificial intelligence, and data analytics, which are tailored to meet the needs of various industries such as financial services, healthcare, and retail. What sets Accenture apart from its competitors is its extensive industry knowledge and ability to deliver comprehensive solutions that address both immediate challenges and long-term goals. The company's aim is to support clients in reducing their environmental impact while driving innovation and growth.

Dublin, IrelandHeadquarters

1989Year Founded

$8.5MTotal Funding

IPOCompany Stage

Consulting, Enterprise Software, CybersecurityIndustries

10,001+Employees

Risks

Rapid AI advancements may outpace Accenture's current capabilities, risking competitive disadvantages.

Integration challenges from multiple acquisitions could affect Accenture's operational efficiency.

The rise of AI-driven startups may disrupt Accenture's market share in customer service solutions.

Differentiation

Accenture's acquisitions enhance its capabilities in digital twin technology for financial services.

The company is expanding its expertise in net-zero infrastructure through strategic acquisitions.

Accenture's focus on software-defined vehicles positions it as a leader in automotive innovation.

Upsides

Accenture's investment in EMTECH supports central bank modernization amid digital currency evolution.

The acquisition of Award Solutions boosts Accenture's presence in the growing 5G and IoT markets.

Accenture's strategic acquisitions align with high-growth markets like digital twins and net-zero projects.

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