Hybrid
Full-Time
Hyderabad, Telangana
India
Skills
Amazon Web Services (AWS)
Computer Science
Data Engineering
Machine Learning
Extract, Transform, Load (ETL)
Data Modeling
Performance Tuning
Big Data
Data Analytics
Amazon Redshift
About the Role
We are seeking a highly skilled Lead Data Engineer to lead the design, implementation, and optimization of scalable data architectures. The ideal candidate will have a deep understanding of data modeling, ETL processes, cloud data solutions, and big data technologies. You will work closely with cross-functional teams to build robust, high-performance data pipelines and infrastructure to enable data-driven decision-making.
Experience: 7 - 12 years
Work Location: Hyderabad (Hybrid)
Mandatory skills: AWS, Python, SQL, Airflow
Responsibilities:
Design and Develop scalable and resilient data architectures that support business needs, analytics, and AI/ML workloads.
Data Pipeline Development: Design and implement robust ETL/ELT processes to ensure efficient data ingestion, transformation, and storage.
Big Data & Cloud Solutions: Architect data solutions using cloud platforms like AWS, Azure, or GCP, leveraging services such as Snowflake, Redshift, BigQuery, and Databricks.
Database Optimization: Ensure performance tuning, indexing strategies, and query optimization for relational and NoSQL databases.
Data Governance & Security: Implement best practices for data quality, metadata management, compliance (GDPR, CCPA), and security.
Collaboration & Leadership: Work closely with data engineers, analysts, and business stakeholders to translate business requirements into scalable solutions.
Technology Evaluation: Stay updated with emerging trends, assess new tools and frameworks, and drive innovation in data engineering.
Required Skills:
Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
Experience: 7 - 10+ years of experience in data engineering
Cloud Platforms: Strong expertise in AWS data services.
Databases: Hands-on experience with SQL, NoSQL, and columnar databases such as PostgreSQL, MongoDB, Cassandra, and Snowflake.
Programming: Proficiency in Python, Scala, or Java for data processing and automation.
ETL Tools: Experience with tools like Apache Airflow, Talend, DBT, or Informatica.
Machine Learning & AI Integration (Preferred): Understanding of how to architect data solutions for AI/ML applications
Experience: 7 - 12 years
Work Location: Hyderabad (Hybrid)
Mandatory skills: AWS, Python, SQL, Airflow
Responsibilities:
Design and Develop scalable and resilient data architectures that support business needs, analytics, and AI/ML workloads.
Data Pipeline Development: Design and implement robust ETL/ELT processes to ensure efficient data ingestion, transformation, and storage.
Big Data & Cloud Solutions: Architect data solutions using cloud platforms like AWS, Azure, or GCP, leveraging services such as Snowflake, Redshift, BigQuery, and Databricks.
Database Optimization: Ensure performance tuning, indexing strategies, and query optimization for relational and NoSQL databases.
Data Governance & Security: Implement best practices for data quality, metadata management, compliance (GDPR, CCPA), and security.
Collaboration & Leadership: Work closely with data engineers, analysts, and business stakeholders to translate business requirements into scalable solutions.
Technology Evaluation: Stay updated with emerging trends, assess new tools and frameworks, and drive innovation in data engineering.
Required Skills:
Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
Experience: 7 - 10+ years of experience in data engineering
Cloud Platforms: Strong expertise in AWS data services.
Databases: Hands-on experience with SQL, NoSQL, and columnar databases such as PostgreSQL, MongoDB, Cassandra, and Snowflake.
Programming: Proficiency in Python, Scala, or Java for data processing and automation.
ETL Tools: Experience with tools like Apache Airflow, Talend, DBT, or Informatica.
Machine Learning & AI Integration (Preferred): Understanding of how to architect data solutions for AI/ML applications