Technical Lead

dentsu Austria

. Design and implement AWS-based data engineering solutions aligned to enterprise standards .

Posted 10/7/2026full-timePune • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AWS-based data engineering solutions, with strong skills in SQL, Python, and data pipeline optimization. Capable of ensuring data solutions meet performance, scalability, and security requirements while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

AWS Data ServicesSQL ExpertisePython ProgrammingData Pipeline OptimizationInfrastructure as Code

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AWS GlueAmazon S3RedshiftAthenaSparkPySparkETL DevelopmentData ModelingPerformance TuningCI/CD Pipelines

Soft Skills

Excellent CommunicationOwnership Mindset

Tools & Technologies

TerraformCloudFormationDockerECSEKS

Certifications & Qualifications

AWS Data Analytics CertificationAWS Solutions Architect Certification

Industry Keywords

Data EngineeringCloud-native Data LakesData Warehouse ArchitecturesBatch Data PipelinesStreaming Data Pipelines

Tech Stack

Tools & technologies

Amazon RedshiftAWSCloudDockerETLPySparkPythonSparkSQLTerraform

About the role

Key responsibilities & impact

Design and implement AWS-based data engineering solutions aligned to enterprise standards
Build and optimize batch and streaming data pipelines using AWS-native and open-source tools
Develop SQL-driven transformations and Python-based data pipelines for analytics use cases
Design efficient data models for performance, scalability, and cost effectiveness
Own data engineering deliverables from development through production support
Perform performance tuning, cost optimization, and capacity planning
Troubleshoot complex data pipeline and production issues, including root-cause analysis
Ensure solutions meet security, reliability, and scalability requirements
Work closely with architects, product owners, and client stakeholders
Translate business and analytics requirements into robust AWS data engineering solutions
Provide technical inputs, estimates, and implementation trade-offs
Contribute to solution discussions and technical design reviews
Follow and contribute to coding standards, documentation, and data engineering best practices
Participate in code reviews and continuous improvement initiatives
Ensure adherence to AWS, security, and compliance guidelines

Requirements

What you’ll need

6 to 10 years of total experience
Strong hands-on experience with AWS data services, including Amazon S3, AWS Glue, Athena, and Redshift
Experience designing cloud-native data lakes and data warehouse architectures on AWS
Deep understanding of batch and streaming data pipelines
Experience building scalable, fault-tolerant data ingestion and transformation workflows
Strong SQL expertise, including complex SQL for transformations, aggregations, performance tuning, and analytics
Hands-on experience handling large-scale datasets in Redshift/Athena
Strong Python programming skills for data engineering use cases
Experience building reusable ETL components, utilities, and data pipelines
Strong understanding of data modeling, transformations, and performance optimization
Hands-on experience with Spark/PySpark or other distributed processing frameworks
Experience working with structured, semi-structured, and unstructured data
Solid understanding of schema design, partitioning, and query optimization
Experience with Infrastructure as Code using Terraform and/or CloudFormation
Hands-on experience building and maintaining CI/CD pipelines for data platforms
Exposure to containerized workloads such as Docker and ECS/EKS
Strong ownership mindset for solution quality, performance, and production stability
Excellent communication skills to collaborate with architects, DevOps, QA, and business stakeholders
Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field
AWS Data Analytics / Solutions Architect certification; any two of the above
Databricks, Snowflake, or other cloud data platform certifications are a plus
Ability to work 12 PM to 9 PM and/or 2 PM to 11 PM IST