Deloitte seeks a Process Mining Consultant to analyze and optimize business processes for clients using technologies like AI/KI, with an emphasis on strategic project involvement at CEO level. The...
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Deloitte seeks a Process Mining Consultant to analyze and optimize business processes for clients using technologies like AI/KI, with an emphasis on strategic project involvement at CEO level. The role’s differentiator is the opportunity to influence top-tier decision-makers early in projects, but there's a risk of over-promising given the broad scope of process analytics and client expectations. The position offers attractive remuneration, though the exact salary isn't specified.
Senior IT-Architect at BWI, the digital backbone for the Bundeswehr, tasked with steering analytics, simulation and AI across a massive federal IT estate. You translate Bundeswehr needs into...
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Senior IT-Architect at BWI, the digital backbone for the Bundeswehr, tasked with steering analytics, simulation and AI across a massive federal IT estate. You translate Bundeswehr needs into end-to-end designs, own architecture concepts and tests, manage service portfolios, and lead enterprise-level architecture work streams that stitch new AI and data solutions into legacy landscapes. The role blends strategic roadmapping with hands-on design, requiring cloud, big-data, and AI fluency, including foundation models and tools like Keras and LangChain. Expect government-grade governance, security, and privacy constraints, plus a demanding partner relationship with the Bundeswehr. It’s an impact-heavy perch with real scale, but the pace is dictated by procurement cycles and ministry process, not venture bets. If you want to shape AI at scale in a security-driven context, this is a rare, high-stakes corridor to do so.
O'Reilly: Building AI Agents with Model Context Protocol (MCP)
Design and implement composable agent architectures using MCP. Understand the MCP architecture and how it enables AI applications to access external context. Build MCP servers that expose tools, resources, and prompts to LLMs.
Databricks Sr. Manager, Engineering for the Identity Platform sounds like a role for someone who wants ownership of a mission-critical, multi-region identity stack without the buzzword sprint. The...
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Databricks Sr. Manager, Engineering for the Identity Platform sounds like a role for someone who wants ownership of a mission-critical, multi-region identity stack without the buzzword sprint. The posting leans into hiring and leadership, process rigor, and cross-team coordination, with a hard requirement of 5+ years in distributed systems and building containerized services. Expect to shepherd high-availability identity services across clouds and products, define roadmaps, and institute architecture reviews and testing regimes. The upside is real influence over reliability at scale and a chance to shape engineering culture; the risk is the usual enterprise tollgate—politics, process, and a vague sense of excellence without concrete tech scope. Databricks lineage: Lakehouse, Spark, Delta Lake, MLflow gives pedigree, but the senior management tilt may detour hands-on work.
Cloud Data Architect AWS / Google Cloud (all genders)
@ adesso-se
DE | 2025-12-25
This role is a misrepresentation of what data engineering entails. The job description claims to focus on cloud data architectures and cloud analytics, but the responsibilities are vague and lack...
read more »
Cloud Data Architect AWS / Google Cloud (all genders)
adesso-se
(DE) FULL TIME | JOB LISTED
This role is a misrepresentation of what data engineering entails. The job description claims to focus on cloud data architectures and cloud analytics, but the responsibilities are vague and lack specificity. It emphasizes collaboration with clients and a culture of innovation, yet fails to detail technical requirements or the actual tasks involved. The mention of AWS and GCP is generic, and the skills required are not clearly defined. The role seems to be more of a client-facing position than a technical data engineering role, with little focus on the core competencies of data pipeline development, infrastructure, and analytics. The company’s reputation as a top IT firm is not substantiated by the job description, which appears to be a marketing effort rather than a genuine technical offering.
Fever markets a Business Growth Analyst role that sounds straight out of a hype brochure: a data-driven, pan-regional growth mandate across up to 40 markets, with big data trenches and 'latest...
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Fever markets a Business Growth Analyst role that sounds straight out of a hype brochure: a data-driven, pan-regional growth mandate across up to 40 markets, with big data trenches and 'latest technology' lifting growth metrics. What stands out is the scope: cross-team influence, direct impact on KPIs, and a genuinely international setting in Madrid. What gives pause: the posting hides the tech stack behind generic terms like big data platforms and analytics tools; no specifics on SQL, Python, Spark, or cloud tech, and no salary data. The role leans on leadership and communication as much as analytics, which can blur the line between analyst and strategist. The Fever brand and a roster of partners add branding upside, yet the lack of concrete tooling and compensation transparency makes this a high-variance bet for a pragmatic data pro.
(Senior) Manager Finance Transformation SAP (Financial Services) (w/m/d)
@ ernstandyoung
DE | 2025-12-23
This role is a misrepresentation of what data engineering entails. The description promotes a consulting firm with a focus on financial services, yet the responsibilities and qualifications seem...
read more »
(Senior) Manager Finance Transformation SAP (Financial Services) (w/m/d)
ernstandyoung
(DE) FULL TIME | JOB LISTED
This role is a misrepresentation of what data engineering entails. The description promotes a consulting firm with a focus on financial services, yet the responsibilities and qualifications seem to align more with a consulting firm’s operations than with data engineering. The job requires leadership in SAP transformations, but lacks specific technical skills in data engineering tools like Apache Spark, Kafka, or cloud platforms. The role emphasizes strategic consulting and partnership with alliances, but offers no clear path for data engineering-specific development or tools. The compensation is unspecified, and the job type is unclear. The description is vague, lacks concrete technical details, and fails to highlight the core competencies of a data engineer.
Masthead is a data reliability platform built for Google Cloud, focused on detecting anomalies and ensuring smooth data pipeline operations. It offers real-time notifications for data issues and pipeline errors without direct access to your sensitive data.
As Zendesk's Senior Data Engineer on the ZAP team, you’ll design scalable ELT pipelines and build robust data models aligning CRM insights with support tooling. The tech bar is high but practical:...
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As Zendesk's Senior Data Engineer on the ZAP team, you’ll design scalable ELT pipelines and build robust data models aligning CRM insights with support tooling. The tech bar is high but practical: SQL-centric modeling with dbt, Python for transforms, and a cloud stack anchored by Snowflake, Redshift/BigQuery, plus Airflow and Kafka for data movement. Expect hands-on work across Kimball and Inmon-style schemas, capacity planning, performance tuning, and cost optimization in large-scale clouds. The Data Stack reads like a mid-market hero list: Snowflake, dbt, Airflow, Kafka, Tableau, Looker, AWS, Kubernetes, Terraform, GitHub Actions. Hybrid work is real, but in-office presence is required part of the week. The role stands out for tangible impact on CRM analytics rather than buzzword compliance; its hurdles are coordination load, opaque leadership signals, and the ever-present risk of over-engineering data pipelines.
Deloitte seeks a Process Mining Consultant to analyze and optimize business processes for clients using technologies like AI/KI, with an emphasis on strategic project involvement at CEO level. The role’s differentiator is the opportunity to influence top-tier decision-makers early in projects, but there's a risk of over-promising given the broad scope of process analytics and client expectations. The position offers attractive remuneration, though the exact salary isn't specified.
Senior IT-Architect at BWI, the digital backbone for the Bundeswehr, tasked with steering analytics, simulation and AI across a massive federal IT estate. You translate Bundeswehr needs into end-to-end designs, own architecture concepts and tests, manage service portfolios, and lead enterprise-level architecture work streams that stitch new AI and data solutions into legacy landscapes. The role blends strategic roadmapping with hands-on design, requiring cloud, big-data, and AI fluency, including foundation models and tools like Keras and LangChain. Expect government-grade governance, security, and privacy constraints, plus a demanding partner relationship with the Bundeswehr. It’s an impact-heavy perch with real scale, but the pace is dictated by procurement cycles and ministry process, not venture bets. If you want to shape AI at scale in a security-driven context, this is a rare, high-stakes corridor to do so.
Databricks Sr. Manager, Engineering for the Identity Platform sounds like a role for someone who wants ownership of a mission-critical, multi-region identity stack without the buzzword sprint. The posting leans into hiring and leadership, process rigor, and cross-team coordination, with a hard requirement of 5+ years in distributed systems and building containerized services. Expect to shepherd high-availability identity services across clouds and products, define roadmaps, and institute architecture reviews and testing regimes. The upside is real influence over reliability at scale and a chance to shape engineering culture; the risk is the usual enterprise tollgate—politics, process, and a vague sense of excellence without concrete tech scope. Databricks lineage: Lakehouse, Spark, Delta Lake, MLflow gives pedigree, but the senior management tilt may detour hands-on work.
Cloud Data Architect AWS / Google Cloud (all genders)
adesso-se
(DE) FULL TIME | JOB LISTED
This role is a misrepresentation of what data engineering entails. The job description claims to focus on cloud data architectures and cloud analytics, but the responsibilities are vague and lack specificity. It emphasizes collaboration with clients and a culture of innovation, yet fails to detail technical requirements or the actual tasks involved. The mention of AWS and GCP is generic, and the skills required are not clearly defined. The role seems to be more of a client-facing position than a technical data engineering role, with little focus on the core competencies of data pipeline development, infrastructure, and analytics. The company’s reputation as a top IT firm is not substantiated by the job description, which appears to be a marketing effort rather than a genuine technical offering.
Fever markets a Business Growth Analyst role that sounds straight out of a hype brochure: a data-driven, pan-regional growth mandate across up to 40 markets, with big data trenches and 'latest technology' lifting growth metrics. What stands out is the scope: cross-team influence, direct impact on KPIs, and a genuinely international setting in Madrid. What gives pause: the posting hides the tech stack behind generic terms like big data platforms and analytics tools; no specifics on SQL, Python, Spark, or cloud tech, and no salary data. The role leans on leadership and communication as much as analytics, which can blur the line between analyst and strategist. The Fever brand and a roster of partners add branding upside, yet the lack of concrete tooling and compensation transparency makes this a high-variance bet for a pragmatic data pro.
(Senior) Manager Finance Transformation SAP (Financial Services) (w/m/d)
ernstandyoung
(DE) FULL TIME | JOB LISTED
This role is a misrepresentation of what data engineering entails. The description promotes a consulting firm with a focus on financial services, yet the responsibilities and qualifications seem to align more with a consulting firm’s operations than with data engineering. The job requires leadership in SAP transformations, but lacks specific technical skills in data engineering tools like Apache Spark, Kafka, or cloud platforms. The role emphasizes strategic consulting and partnership with alliances, but offers no clear path for data engineering-specific development or tools. The compensation is unspecified, and the job type is unclear. The description is vague, lacks concrete technical details, and fails to highlight the core competencies of a data engineer.
As Zendesk's Senior Data Engineer on the ZAP team, you’ll design scalable ELT pipelines and build robust data models aligning CRM insights with support tooling. The tech bar is high but practical: SQL-centric modeling with dbt, Python for transforms, and a cloud stack anchored by Snowflake, Redshift/BigQuery, plus Airflow and Kafka for data movement. Expect hands-on work across Kimball and Inmon-style schemas, capacity planning, performance tuning, and cost optimization in large-scale clouds. The Data Stack reads like a mid-market hero list: Snowflake, dbt, Airflow, Kafka, Tableau, Looker, AWS, Kubernetes, Terraform, GitHub Actions. Hybrid work is real, but in-office presence is required part of the week. The role stands out for tangible impact on CRM analytics rather than buzzword compliance; its hurdles are coordination load, opaque leadership signals, and the ever-present risk of over-engineering data pipelines.
