Data Analytics Engineer

Role:

: Data Analytics Engineer (AI/ ML FOCUS)

Location:

Sunnyvale, CA Salary Range:

$70,000-$125,000 a year

Desired Skills:

Artificial Intelligence | Data Analytics | Kafka | Machine Learning | Python | SQL |

Apache Spark Job Description:

Responsibilities Data Pipeline & Infrastructure Development:

Build, maintain, and scale data pipelines (ETL or ELT) using tools like Apache Spark, Airflow, and Kafka to support AI and ML workloads.

AI Ready Data Preparation:

Transform messy, unstructured data (text, images, video) into structured datasets suitable for model training, including handling feature engineering and vector database ingestion.

ML Model Product ionization:

Partner with data scientists to deploy ML models, create APIs for models, and implement MLOPS practices, including monitoring for data drift.

Analytics and Visualization:

Create dashboards (Tableau, Power BI, Looker) and run SQL queries to provide actionable business insights, acting as an analytics engineer.

Data Governance & Quality:

Ensure data quality, reliability, and security (PII or PHI) within AI systems, ensuring compliance with regulations like GDPR or HIPAA.

Cloud and Data Management:

Operate within cloud environments (AWS, Azure, Google Cloud) using services like S3, Redshift, Glue, or Databricks.

Key Skills and Qualifications Programming Languages:

Expert level Python and Advance SQL are mandatory. Java or Scala are preferred for large scale distributed systems.

ML Frameworks:

Familiarity with libraries such as PyTorch, TensorFlow, or Scikit learn for data manipulation and model interaction.

Data Engineering Tools:

Experience with Apache Spark, Kafka, Airflow, dbt, and Vector Databases (Pinecone, Milvus).

Cloud Platforms:

Hands on experience with AWS (Glue, SageMaker) or Google Cloud Platform.

Analytical Skills:

Strong ability to perform exploratory data analysis (EDA) and interpret complex datasets.

Soft Skills:

Must have Strong communication to bridge technical data engineering with business stakeholders.