Consultant – Data & Analytics

Consultant – Data & Analytics

Are you passionate about data analytics and transformation? Do you thrive on developing data-driven solutions that empower businesses to achieve measurable success? If tackling challenges and delivering creative, impactful outcomes excites you, Synogize wants to connect with you!

We’re seeking an experienced consultant to join our growing team of Data & Analytics professionals in Melbourne/Sydney. To be eligible, applicants must have full working rights in Australia and a minimum of 3 years of industry experience in Data & Analytics.

About You

You are someone who:

• Enjoys collaborating with clients to design tailored analytics solutions.
• Thrives on solving technical challenges and optimizing data use.
• Has a deep understanding of business problems and turns them into actionable insights and data models.
• Seeks a long-term role that fosters both personal and company growth.
• Delivers exceptional client experiences that add tangible business value.
• Is committed to continuous learning and staying updated on the latest tools and trends in data analytics.
• Has 3-5 years of experience in data analytics with a proven track record of driving customer success through data solutions.

Key Responsibilities

• Data Modeling: Design, build, and maintain scalable data models for internal and client-specific analytics.
• ETL Development: Collaborate with data engineers to create efficient ETL/ELT pipelines, transforming raw data into usable datasets.
• Data Transformation: Use tools like dbt and coleasce for SQL-based transformations, delivering organized datasets for analysis.
• Analytics Solutions: Ensure seamless integration of analytics tools (e.g., Tableau, Power BI, Looker) with data sources in collaboration with data analysts and BI teams.
• Data Quality & Governance: Maintain data accuracy through automated testing and data governance protocols.
• Client Engagement: Partner with clients to understand their challenges and translate them into technical solutions.
• Collaboration: Work closely with data scientists, engineers, and business stakeholders to support data-driven decision-making.
• Performance Optimization: Continuously monitor and improve the scalability and efficiency of data pipelines and models.

Required Skills & Experience

• Proficiency in SQL and experience with modern data transformation tools (e.g., dbt, Coalesce).
• Experience with cloud platforms like Snowflake, BigQuery, Fabric, or Databricks.
• Advanced SQL skills (5+ years), including expertise in complex queries, stored procedures, and managing views.
• Strong understanding of ETL/ELT processes.
• Ability to build compelling data visualizations and dashboards using Tableau, Power BI, or Looker.
• Excellent communication skills for explaining complex technical concepts to non-technical audiences.
• Proven experience in designing and maintaining real-time analytics solutions.

Bonus Skills

• Familiarity with machine learning or advanced data science techniques.
• Passion for creating intuitive data visualizations that tell compelling stories.
• Experience with data governance, ensuring data quality, security, and accuracy.

Required Qualifications

• Valid permanent work visa, permanent residency, or Australian citizenship.
• A Bachelor’s or Graduate Degree in Computer Science, Data Science, Information Technology, or a related field.

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.