Job Summary

We are seeking an experienced Analytics Engineer to join our growing Data & Analytics team. In this role, you will bridge the gap between Data Engineering and Business Intelligence by designing, building, and maintaining reliable, scalable, and high-quality data models that empower data-driven decision-making across the organization.

The ideal candidate has strong experience with SQL, dbt, modern cloud data warehouses, ETL/ELT pipelines, and business intelligence tools. You will collaborate closely with Data Engineers, Data Scientists, Product Managers, and Business Stakeholders to transform raw data into trusted analytical datasets and actionable insights.

Key Responsibilities

• Design, develop, and maintain scalable analytical data models using dbt and SQL.
• Build and optimize ELT/ETL pipelines for reliable data transformation.
• Develop semantic data models that support business reporting and self-service analytics.
• Collaborate with Data Engineers to improve data architecture and warehouse performance.
• Partner with Data Scientists to provide clean, analytics-ready datasets for machine learning initiatives.
• Create and maintain business metrics, KPIs, and data definitions across departments.
• Optimize SQL queries and improve warehouse performance for large-scale datasets.
• Implement automated testing, monitoring, and documentation for data pipelines.
• Ensure data accuracy, consistency, governance, and compliance with organizational standards.
• Support dashboard development using Power BI, Tableau, or Looker.
• Troubleshoot data quality issues and resolve pipeline failures.
• Maintain comprehensive documentation for data models, pipelines, and business logic.
• Participate in code reviews and promote engineering best practices.
• Work with cross-functional teams to identify new reporting and analytics opportunities.
• Continuously improve analytics infrastructure using modern data engineering methodologies.

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Information Systems, Mathematics, Statistics, Engineering, or a related field.
• 3+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence.
• Advanced proficiency in SQL and relational databases.
• Hands-on experience with dbt (Data Build Tool).
• Experience with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Azure Synapse.
• Experience building ETL/ELT pipelines.
• Knowledge of dimensional modeling (Star Schema, Snowflake Schema).
• Familiarity with Git version control and CI/CD workflows.
• Experience with business intelligence platforms such as Tableau, Power BI, or Looker.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Python for data processing and automation.
• Knowledge of Apache Airflow or similar workflow orchestration tools.
• Familiarity with Spark or Databricks.
• Experience working with large-scale cloud data platforms.
• Understanding of data governance, security, and privacy best practices.
• Experience supporting machine learning and AI workflows.
• Relevant certifications in cloud platforms or analytics technologies.

Technical Skills

Programming

• SQL
• Python
• Git

Data Warehousing

• Snowflake
• Google BigQuery
• Amazon Redshift
• Azure Synapse Analytics

Data Transformation

• dbt
• ETL/ELT
• Data Modeling
• Data Validation

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Business Intelligence

• Power BI
• Tableau
• Looker

Workflow & Automation

• Apache Airflow
• CI/CD
• GitHub Actions

Preferred Soft Skills

• Excellent communication and presentation skills
• Strong analytical thinking
• Attention to detail
• Problem-solving mindset
• Cross-functional collaboration
• Time management
• Project ownership
• Continuous learning mindset

Benefits

• Competitive salary and annual performance bonus
• Medical, Dental, and Vision insurance
• Paid Time Off (PTO) and company holidays
• Flexible remote/hybrid work options
• Professional development and certification reimbursement
• Employee wellness programs
• Career growth opportunities
• Collaborative and innovative work environment