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Lead Data Engineer - ETL/SQL (7-12 yrs)

7-12 years

Lead Data Engineer - ETL/SQL (7-12 yrs)

Blumetra

posted 3d ago

Job Role Insights

Flexible timing

Job Description

Job Summary :

We are seeking a highly skilled Lead Data Engineer/Associate Architect 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, DBT.


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.


Big Data Technologies : Experience with Hadoop, Spark, Kafka, and related frameworks.


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.



Functional Areas: Software/Testing/Networking

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