Job Description

Senior Consultant - Data & Analytics

Are you a seasoned data analytics professional who excels in developing data-driven solutions? Do you have a passion for leading transformational initiatives that deliver measurable business success? If solving complex challenges and driving innovative outcomes excites you, Synogize wants to meet you!

We’re seeking a Senior Consultant with a deep understanding of Data & Analytics to join our dynamic team in Melbourne/Sydney. To be considered, candidates must have full, permanent working rights in Australia and at least 5+ years of industry experience in Data & Analytics.

About You

You are someone who:

• Collaborates closely with clients, designing tailored analytics strategies to solve complex business challenges.
• Leads technical problem-solving efforts, optimizing data to deliver impactful insights.
• Transforms business needs into actionable data models that drive strategic decision-making.
• Is excited by the opportunity to mentor junior team members and play a key role in company growth.
• Delivers outstanding client results with tangible business value.
• Is dedicated to continuous improvement and keeps up with the latest tools and trends in data analytics.

Key Responsibilities

• Data Modeling & Architecture: Design, build, and maintain scalable data models that meet both client and internal needs.
• ETL Development: Oversee the development of robust ETL/ELT pipelines, transforming raw data into structured, analyzable datasets.
• Data Transformation: Lead SQL-based transformations using tools like dbt and Coalesce, delivering clean datasets for analysis.
• Analytics Solutions: Integrate and manage analytics platforms (e.g., Tableau, Power BI, Looker) with data sources, working closely with BI and data teams.
• Data Quality & Governance: Implement data governance frameworks to ensure data accuracy and integrity.
• Client Leadership: Guide clients through technical challenges and deliver high-impact solutions that meet business goals.
• Cross-functional Collaboration: Work with data scientists, engineers, and business stakeholders to drive data-driven decision-making.
• Performance Optimization: Monitor and improve the scalability and performance of data models and pipelines.

Required Skills & Experience

• Advanced SQL expertise (5+ years) with strong experience in complex queries, stored procedures, and managing large datasets.
• Hands-on experience with cloud platforms like Snowflake, BigQuery, Fabric, or Databricks.
• Mastery of ETL/ELT processes and modern data transformation tools (e.g., dbt, Coalesce).
• Expertise in creating compelling data visualizations using tools like Tableau, Power BI, or Looker.
• Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders.
• Proven ability to deliver real-time analytics solutions in dynamic environments.

Bonus Skills

• Machine learning or advanced data science techniques.
• Passion for data storytelling and creating engaging visualizations.
• Experience in data governance and ensuring data security, quality, and accuracy.

Required Qualifications

• Must hold a valid permanent work visa, permanent residency, or Australian citizenship.
• Bachelor's or Graduate's Degree in Information Technology, Computer Science, Computer Engineering, Software Engineering, Applied math, Statistics, Physics, or equivalent experience.

About Synogize

At Synogize, we harness synergy and passion to drive success. Founded by Data & Analytics professionals, we pride ourselves on bridging the gap between people, processes, and technology to deliver innovative solutions. Our mission is to create transformative outcomes by aligning data, technology, and talent, helping organizations shape the future of innovation.

Next Steps

If this opportunity excites you, we’d love to hear from you! Please apply by submitting your resume.

Note to Recruitment Agencies: We have this role covered and do not accept unsolicited CVs. We are not responsible for any fees related to unsolicited resumes. Thank you.