Senior Data Engineer

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent and innovation-led company serving clients in more than 120 countries. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

What’s in it for you?

Work-Life Balance: Hybridworkingmodel / Flexiblehours/ Birthdayoff/ No dresscode/ HappyHours

Health& Wellness: Life & HealthInsurance/ An EmployeeAssistance & WellnessProgram

Transportation: Shuttleservice / Transportationsupport

Financial Benefits: Meal allowance/ EmployeeReferralBonus Program / Performancebonus & promotion/ Accenture RecognitionPoints

Professional Development: Learning budget/ PersonalcareerdevelopmentwithPeople Leads/ Buddy Program

WorkEnvironment: Workingon internationalprojectswitha globallydiverseteam/ A fast-pacedtechnologyenvironment

Role Overview

We are looking for a Senior Data Engineer to join our Data & AI team and take ownership of designing, developing, and optimizing scalable data solutions.

In this role, you will work closely with Data Architects, Data Scientists, Business Analysts, and other engineering teams to transform complex data requirements into reliable, scalable, and high-performing data pipelines and data products.

You will play a key role in building modern data platforms, implementing data ingestion and transformation pipelines, ensuring data quality, and making trusted data available for analytics, reporting, and AI use cases.

Key Responsibilities

- Design, develop, and maintain scalable data pipelines and data processing solutions using Python, SQL, and Apache Spark/PySpark

- Build and optimize batch and, where required, near-real-time data ingestion and transformation pipelines

- Design and implement scalable data models and curated datasets for analytics and AI use cases

- Work with modern cloud platforms (Azure, AWS, or GCP) and lakehouse/data warehouse architectures, including platforms such as Databricks and Snowflake

- Implement data transformation and processing patterns

- Develop and maintain data quality, validation, monitoring, and error-handling mechanisms

- Optimize data pipelines for performance, scalability, and cost efficiency

- Collaborate with Data Architects and Product Owners to translate technical decisions and business requirements into production-ready implementations

- Own the reliability and operational performance of production data pipelines, including monitoring, troubleshooting, incident resolution, and root-cause analysis

- Conduct code and design reviews and ensure engineering best practices are followed

- Mentor and support junior and mid-level Data Engineers

Required Qualifications & Skills

- BSc or MSc degree in Computer Science, Computer Engineering, Data Engineering, Data Science, Artificial Intelligence, or a related fields

- 5+ years of professional experience in Data Engineering, with strong experience in data integration, data processing, and analytics

- Strong hands-on experience with Python and SQL

- Experience with Apache Spark / PySpark or similar distributed data processing tools is a strong plus

- Proven experience designing and implementing data pipelines

- Strong understanding of data modeling, data warehousing, and data lake/lakehouse architectures

- Experience with data pipeline orchestration, scheduling, dependency management, and failure/reprocessing strategies

- Experience working with relational databases and large-scale data platforms

- Hands-on experience with cloud platforms, particularly AWS, Azure, or GCP

- Experience supporting AI/ML workloads, LLM integrations, or AI-powered applications is a strong plus

- Experience with Git and CI/CD practices

- Strong analytical, problem-solving, and communication skills

Preferred Qualifications

- Relevant certifications in data engineering or cloud technologies, such as Databricks, Microsoft Azure, AWS, or Google Cloud certifications

- Experience working with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or Azure Synapse

- Experience with cloud-native data services such as Azure Data Factory, AWS Glue, or equivalent technologies

- Experience with Apache Kafka, Azure Event Hubs, or other streaming and event-driven data processing technologies

- Experience with Apache Airflow or other workflow orchestration tools

- Understanding of Data Governance, Data Catalog, metadata management, data lineage, data quality, and data security concepts

- Experience with data architecture and enterprise data platform design

- Knowledge of data visualization and business intelligence tools such as Power BI, Amazon QuickSight, or equivalent platforms

- Experience with automation tools or AI-assisted development workflows

Ready tomakean impact? Ifyouareexcitedaboutworkingwithcutting-edgetechnologyandparticipatingin thrillinginternationalprojects, wewanttohearfromyou! JoinAccenture andachieveyourgoals.

#GreatPlaceToWork

Location: Teknopark Istanbul (Kurtköy) Hybrid: 3 days office per week

ApplyNow!

About Accenture

Visit us atwww.accenture.com

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