Working Hours : Full Time
Experience : 4–6 Years
Soothsayer Analytics is a global AI & Data Science consultancy headquartered in Detroit, with a thriving delivery center in Hyderabad. We design and deploy end-to-end custom Machine Learning & GenAI solutions—spanning predictive analytics, optimization, NLP, and enterprise-scale AI platforms—that help leading enterprises forecast, automate, and gain a competitive edge.
As a Data Engineer, you will build the foundation that powers these AI systems—scalable, secure, and high-performance data pipelines.
We seek a Data Engineer (Mid-level) with 4–6 years of hands-on experience in designing, building, and optimizing data pipelines. You will work closely with AI/ML teams to ensure data availability, quality, and performance for analytics and GenAI use cases.
Data Pipeline Development
Build and maintain scalable ETL/ELT pipelines for structured and unstructured data.
Ingest data from diverse sources such as APIs, streaming, and batch systems.
Data Modeling & Warehousing
Design effective data models to support analytics and AI workloads.
Develop and optimize data warehouses/lakes using Redshift, BigQuery, Snowflake, or Delta Lake.
Big Data & Streaming




Work with distributed systems like Apache Spark, Kafka, or Flink for real-time and large-scale data processing.
Manage feature stores for machine learning pipelines.
Work closely with Data Scientists and ML Engineers to ensure high-quality training data.
Implement data quality checks, observability, and governance frameworks.
Bachelor's or Master's in Computer Science, Data Engineering, or related field.
Experience: 4–6 years in data engineering with expertise in:
Programming: Python, Scala, or Java (Python preferred)
Big Data & Processing: Apache Spark, Kafka, Hadoop
Databases: SQL and NoSQL (Postgres, MongoDB, Cassandra)
Data Warehousing: Snowflake, Redshift, BigQuery, or similar
Cloud Platforms: AWS, Azure, or GCP (data services)
Feature engineering, embeddings, vector databases
Skill Details Last Used Experience (Months) Self-Rating (0–10) Python SQL / NoSQL Apache Spark Kafka Data Warehousing (Snowflake, Redshift, etc.) Cloud (AWS / Azure / GCP) Data Quality / Governance Tools MLOps / LLMOps GenAI Integration
Provide a detailed resume highlighting end-to-end data engineering projects.

📌 Data Engineer - ML & AI (Secunderabad)
🏢 Soothsayer Analytics
📍 Secunderabad