Data Engineer

4 weeks ago


Ahmedabad, India Havoc Consultants Full time

Responsibilities :

Design and Development :

- Design, implement, and optimize complex data pipelines for large-scale data processing and transformation.

- Develop data models and schemas to ensure data consistency, accuracy, and scalability.

- Build and maintain data warehouses, data lakes, and other data storage solutions.

Cloud Technologies :

- Leverage cloud platforms (AWS, Azure, GCP) for data processing, storage, and analytics.

- Implement and manage cloud-based data infrastructure (e.g., EMR, Data bricks, Redshift).

ETL Processes :

- Develop and maintain efficient Extract, Transform, Load (ETL) processes to ingest and integrate data from diverse sources.

- Ensure data quality, integrity, and security throughout the ETL pipeline.

Collaboration :

- Work closely with data scientists, analysts, and business stakeholders to understand requirements and deliver data solutions that drive business value.

- Clearly communicate technical concepts to non-technical audiences.-

Performance and Optimization :

- Monitor data pipeline performance and identify opportunities for optimization.

- Implement performance tuning techniques to enhance data processing efficiency.

Qualifications :

Experience :


- 5+ years of experience in data engineering roles, preferably with exposure to the banking or financial services sector.

Technical Skills :

- Strong proficiency in SQL and Python or another scripting language.

- Expertise in data modelling, schema design, and data warehousing principles.

- Experience with cloud platforms (AWS, Azure, GCP) and cloud-based data tools.

- Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.

- Knowledge of ETL tools and data pipeline frameworks (e.g., Apache Airflow).


Soft Skills :

- Excellent problem-solving and analytical skills.

- Strong communication and interpersonal skills, including the ability to collaborate effectively with cross-functional teams.

- Ability to work independently and as part of a team.

(ref:hirist.tech)

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