Analytics Engineer

As an Analytics Engineer, you will be responsible for transforming raw data from our applications into structured datasets for large-scale analysis and machine learning models. You will work closely with our development, data science, and business intelligence teams to ensure data integrity, quality, and accessibility.

Educational Background:

Bachelor's degree in computer science, Data Engineering, or a related field.

Experience:

3+ years of experience as an Analytics Engineer or in a similar role.

Strong Communication skills:

Ability to work with technical and non-technical audiences to translate business requirements into data models.

Technical Proficiency:

Data Warehousing:

Knowledge of data warehousing concepts and solutions (e.g., Redshift, Snowflake).

Data modeling:

experience in modern data modeling practices, ideally dimensional modeling.

Programming Languages:

Proficiency in SQL and a familiarity with Python.

Data Processing:

Experience with ETL tools and frameworks (e.g., Apache Airflow, Luigi, DBT).

Database Management:

Strong knowledge of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra).

Version Control:

Proficient with version control systems (e.g., Git).

Machine Learning:

Understanding of machine learning concepts and experience working with data for ML model training.

AI:

Familiarity and enthusiasm for bleeding-edge analytical enablement using tools such as Large Language Models and Prompt Engineering.

Data Modeling :

Research and work with business stakeholders to develop our data warehouse model.

Data Transformation:

Clean, transform, and enrich data to create high-quality datasets suitable for analysis and machine learning.

Collaboration:

Work closely with product teams, software developers, data scientists, and analysts to understand data needs and deliver innovative solutions.

Data Management:

Ensure data accuracy, consistency, and reliability across all datasets.

Optimization:

Optimize data processes for performance and scalability.

Documentation:

Maintain comprehensive documentation of transformation logic and lineage.