A hands-on leader who designs and delivers enterprise-scale data platforms and pipelines for Fortune 500 and large global enterprises, owning technical architecture on active engagements while anchoring solutioning, proposals, and technical discovery on new pursuits.
Responsibilities
Architect and build end-to-end data platforms for large enterprise customers: ingestion, lakehouse/warehouse modeling, transformation pipelines, orchestration, and serving layers for BI and AI/ML workloads
Lead delivery teams of data engineers — set technical direction, review designs and code, and own quality of what ships
Design for enterprise realities: data governance, lineage, security, cost optimization, and SLAs at scale
Build AI-ready data foundations — pipelines and semantic layers that feed RAG, agentic, and ML use cases
Lead technical discovery and architecture conversations with customer-side senior/enterprise architects, CISOs, and CDOs
Build and deploy AI solutions for clients across BCG regions, partnering with multidisciplinary teams and leading thought leadership in scientific communities.
Compensation
The base salary for this role is at least EUR 54.000,00. Employees may also be eligible for an annual discretionary performance bonus.
Responsibilities
Apply software development practices and standards to develop robust and maintainable software
Actively involved in every part of the software development process
Guide non-technical teams and consultants in best practices for robust software development
Optimize and enhance computational efficiency of algorithms and software design
Collaborate in teams to share software design and solution ideas
Requirements
Master’s or PhD degree program in Computer Research Science, Data Science, Statistics, Operations Research, or related field
Senior Databricks Data Engineer responsabile della progettazione, sviluppo e implementazione di pipeline di dati scalabili e performanti, coordinando l’ottimizzazione dei carichi di lavoro in collaborazione con Data Scientist e Data Architect.
Compensation
Per questa posizione è prevista una RAL (retribuzione annua lorda) compresa tra € 33.000 e € 40.000.
Responsibilities
Progettare, sviluppare e implementare pipeline di dati scalabili e performanti
Coordinare l’ottimizzazione dei carichi di lavoro
Guidare il design dell’architettura Medallion e la gestione dei Delta Lake
Garantire la qualità dei processi di ingestione e trasformazione
Collaborare con Data Scientist e Power BI Developer
Lead client engagements, co-design data engineering solutions through close collaboration with clients, manage stakeholders, and ensure impactful project delivery from strategy through execution.
Compensation
Competitive salary package, including annual salary increase, bonuses, and flexible mobility options (company car or personalized mobility plan).
Responsibilities
Building robust, scalable data pipelines and architectures to enable efficient ingestion, processing, and delivery of large volumes of structured and unstructured data.
Designing and implementing data solutions leveraging modern cloud platforms (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark, Kafka).
Developing logical and physical data models and optimizing database solutions for various data types and workloads, including relational, NoSQL, time-series, and graph databases.
Implementing best practices for batch, streaming, and real-time data integration, adapting to structured, semi-structured, and unstructured data sources.
Enabling continuous integration and deployment of data services and infrastructure, using modern DevOps tooling to ensure reliability, versioning, and automation in data workflows.
Requirements
WO Master's degree in Data Science
WO Master's degree in Econometrics
WO Master's degree in Applied Mathematics
WO Master's degree in Computer Science
WO Master's degree in (Energy) Engineering
Senior MLOps Engineer
Aligned Automation Services Pvt Ltd · Posted Nov 11, 2026
Design, build, and maintain scalable, reliable batch and streaming data pipelines using modern distributed frameworks (e.g., Spark, Flink, Kafka, Airflow).
Responsibilities
Design, build, and maintain scalable, reliable batch and streaming data pipelines using modern distributed frameworks (e.g., Spark, Flink, Kafka, Airflow).
Architect robust data models and storage strategies optimized for analytical query performance in cloud data warehouses and data lakes (e.g., Snowflake, BigQuery, AWS S3/Redshift).
Monitor data pipeline health, establish automated testing and data validation frameworks, and optimize pipeline throughput, latency, and query performance.
Ensure all data management practices strictly comply with security protocols, privacy standards, and regulatory frameworks required for financial infrastructure.
Partner with Analytics, Data Science, Product, and Infrastructure teams to translate raw protocol and product telemetry into canonical, reliable data platforms.
Develop, automate, and maintain resilient data pipelines connecting on‑premises laboratory equipment, high‑throughput test benches, and edge systems to Microsoft Azure.
Responsibilities
Develop, automate, and maintain resilient data pipelines
Investigate, unpack, and parse complex, non‑standard, binary, proprietary, and undocumented file formats
Implement parsers and normalization routines for diverse technical data streams
Clean, validate, and transform fragmented or schema‑less raw data into optimized, partitioned Lakehouse tables
Deploy, monitor, and maintain pipeline resources on Azure using Terraform, Databricks, and containerized workflows
Requirements
BSc, MSc or Ph.D. in Data Engineering, Computer Science, Software Engineering, Applied Physics, Electrical Engineering, or a related field.
Seeking an experienced Snowflake Data Engineer with 5+ years of data engineering experience to design, develop, and optimize cloud-based data storage, processing, and integration solutions.
Responsibilities
Develop and optimize cloud based data storage and processing solutions using Snowflake.
Design, implement, and maintain robust data pipelines and ETL processes.
Collaborate with federated teams and data engineers to understand requirements and deliver high quality data solutions.
Ensure data integrity and security across all workflows and storage solutions.
Monitor and troubleshoot data pipelines to ensure accuracy and reliability.
Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Design, deploy, and maintain production-grade Amazon EKS clusters architected for petabyte-scale data processing with high availability and fault tolerance
Operate in air-gapped private VPC environments without internet access, managing secure package repositories and container registries
Debug and resolve complex distributed systems issues across EKS, Karpenter, and Spark, including scheduling bottlenecks, node scaling delays, and cascading failures under heavy load
Implement Karpenter consolidation and disruption policies balancing cost optimization with job resiliency
Manage spot and on-demand instance strategies with robust node interruption handling
Requirements
Bachelor's degree in Computer Science, Information Systems or related discipline
Nice to have: Kubernetes certification (CKA, CKAD, or CKS)
Nice to have: AWS certifications
Nice to have: Active contributions to open-source Kubernetes, Karpenter, or Spark projects
Senior Data ArchitectNewAccellor · Hyderabad
Forward Deployed AI EngineerNewBoston Consulting Group · Milano, Italy
Senior Databricks Data EngineerNewSopra Steria · Roma, Italy
Senior MLOps EngineerNewAligned Automation Services Pvt Ltd · Indore, India