Data Engineer Consultant | Hybrid | Netherlands | €77K–€88K + €3K Bonus

Job Title: Data Engineer Consultant

Location: Netherlands (Hybrid - 2 days office, 3 days home)
Industry: Data Engineering
Compensation: €77,472 - €87,840 per year (€3,200 - €4,000 monthly)
Monthly Bonus: €3,000
Working Hours: Minimum 36 hours per week
Vacation Days: 25
Mobility Budget: €450 monthly
Visa Sponsorship: Not Available
Languages Required: Fluent Dutch and English
Relocation Assistance: Not Available
Holidays: 25

Job Description

As a Data Engineer Consultant, your primary responsibility is to prepare data for analytical or operational use. You will build data pipelines to bring together information from different source systems. You will integrate, consolidate, and clean the data before structuring it for use in analytical applications.

While working on challenging assignments with our clients, we also focus on your professional growth. We believe in helping you discover and unlock your potential through coaching, training, and sharing knowledge. This enables you to continue developing as a professional and helps us serve our clients even better.

Ideal Candidate

The ideal candidate should possess deep knowledge of data engineering and data modeling, both conceptually and dimensionally. You should have experience with various cloud architectures, such as Microsoft Azure or AWS, and be familiar with working in Scrum, Agile, and DevOps methodologies. You should be proficient in technologies such as Databricks, Spark Structured Streaming, and PySpark, and be capable of translating user requirements into appropriate solutions. Additionally, you should be skilled in analyzing source data and designing effective data models.

Key Responsibilities

• Data Engineering: Build and maintain data pipelines, integrate data from various source systems, and structure it for analytical purposes.

• Data Modeling: Apply conceptual and dimensional data modeling techniques to ensure data can be leveraged effectively.

• Technology Application: Use Databricks, Spark, and PySpark to build robust data solutions.

• Collaboration: Work within Scrum and Agile teams to develop data solutions that meet business needs.

Skills & Qualifications

Must-Have Skills

• Data Engineering

• Data Modeling

• Scrum, Agile, DevOps methodologies

• Python

• MySQL

• Microsoft Azure

• Bachelor’s degree (HBO or equivalent)

• Fluency in Dutch

Preferable Skills

• Databricks

• Microsoft Power BI

• Azure Data Factory

• Data Vault

• Data Governance

• Bachelor’s degree in Data Science (BSc) or Computer Science (BSc)

• Data Engineering on Microsoft Azure (DP-203) certification

• Proficiency in English

Soft Skills

• Strong communication skills

• Adaptability

• Teamwork and collaboration

• Problem-solving abilities

• Self-driven and motivated

Experience

• More than 5 years of experience working in complex data environments at top 500 companies.

Compensation & Benefits

• Annual Salary: €77,472 - €87,840

• Monthly Salary: €3,200 - €4,000

• Monthly Bonus: €3,000

• Mobility Budget: €450

• Extra Benefits: Pension package, phone, expenses reimbursement, lease budget, and laptop.

Working Conditions

• Hybrid Work: 2 days in the office, 3 days remote

• Vacation: 25 days off per year

• Visa Sponsorship: Not available

• Relocation Assistance: Not available

• Working Hours: Minimum of 36 hours per week

Enterprise Analytics Manager, Houston, TX - $140,000 - $180,000

Enterprise Analytics Manager, Houston, TX
Full-Time, Permanent
$140,000 - $180,000
10/20% Bonus + Benefits

MINIMUM QUALIFICATIONS

Education:

• Bachelor’s Degree in Information Systems, Computer Science, Data Science, Business Analytics, or equivalent experience required.

Licenses/Certifications:

• None required.

Experience / Knowledge / Skills:

• Minimum of five (5) years of experience in analytics and information systems, including at least three (3) years in a leadership role.

• Strong oral and written communication skills.

• Customer-focused with a collaborative mindset.

• Results-oriented, capable of thriving in a fast-paced environment and managing multiple projects.

• Excellent interpersonal and time management skills.

• Familiarity with business intelligence tools, data science tools, and dashboard software, including but not limited to:

• Database and Query Languages: SQL, Nomad, Oracle, Vertica, Snowflake

• Visualization Tools: Tableau (preferred), Spotfire, Sisense, Qlik, Microsoft Power BI

• Data Visualization Server Admin Tools: Tableau Core, Data Management Server

• Data Prep/Transformation Tools: Tableau Prep, Hadoop, Alteryx, Trifacta, Talend

• Statistical Tools: R, SAS, SPSS, Matlab, Minitab

• Data Science Tools: Python, R, SAS, dataiku, DataRobot, Anaconda

PRINCIPAL ACCOUNTABILITIES

• Align departmental initiatives with organizational goals to support strategic objectives.

• Lead, motivate, and oversee teams responsible for data collection, modeling, analysis, and insights to drive value.

• Foster transparent communication through departmental and cross-functional meetings with key stakeholders.

• Manage resource needs and promote professional growth within the team by setting and tracking performance goals and development plans.

• Oversee and prioritize analytics requests, strategically managing timelines, deliverables, and resource allocation.

• Collaborate with executive leadership to deliver data-driven insights that align with enterprise goals and priorities.

• Monitor and manage budgets related to analytics projects or operations.

• Serve as an advisor to leadership on analytics strategy and data-driven decision-making.

• Build and maintain relationships with internal and external customers, vendors, and regulatory agencies.

• Oversee the design and delivery of analytics solutions that enable informed decision-making through operational metrics.

• Provide timely updates and executive summaries to leadership and stakeholders.

• Act as a mentor and coach, fostering a culture of collaboration and continuous improvement.

• Establish quality controls and standards to meet organizational expectations and regulatory requirements.

• Ensure compliance with policies, including security, access control, and data privacy standards (e.g., HIPAA).

• Manage foundational analytics tools and systems, ensuring availability, growth, and support.

• Administer and oversee the onboarding of data into the Enterprise Data Warehouse Platform, as well as third-party data submissions.

• Support the growth of analytics capabilities across the organization by promoting transparency and usage of existing tools and products.

• Mentor and train analytics user groups in tools such as Tableau, Business Objects, and SQL.

• Encourage adoption of data-driven decision-making through existing analytical products.

OTHER EXPECTATIONS

• Adhere to organizational policies, procedures, and standards related to quality, productivity, and resource management.

• Promote professional growth through continuing education and skills development.

• Serve as a mentor and resource for less experienced staff.

• Demonstrate a commitment to personalized and efficient service for all stakeholders.

Other duties as assigned.

This version removes specific organizational references and rewrites certain sections to ensure uniqueness. Let me know if additional adjustments are needed!