Python Developer
4 days ago
Algoleap is one of the fastest growing digital engineering services company based out of Hyderabad working with many fortune 1000 customers in transforming their digital landscape.
At Algoleap, we believe that a truly innovative and successful workplace is one where diversity, equity, and inclusion thrive. We are dedicated to building a team that celebrates unique perspectives and experiences, fostering an environment where everyone is empowered to succeed. Algoleap offers compelling full-time roles designed to help you grow and excel. Our positions come with flexible options, including onsite and hybrid roles, allowing our team members to work closely with our clients and make a direct impact on the engagements at the same time offering great work life balance.
Job Description:
A "Python Data Engineer" is a technical role focused on designing, building, and maintaining data pipelines using primarily Python programming language to extract, transform, and load (ETL) data from various sources into a usable format for analysis, often working with large datasets and collaborating with data scientists and analysts, while utilizing cloud platforms and data warehousing technologies to ensure efficient data processing and storage; requiring strong proficiency in Python libraries like Pandas, NumPy, and potentially distributed computing frameworks like Apache Spark.
Key responsibilities:
- Data Pipeline Development: Design and implement robust data pipelines using Python to extract data from different sources (databases, APIs, flat files), transform it as needed, and load it into data warehouses or data lakes.
- ETL Process Automation: Write Python scripts to automate data cleansing, aggregation, and manipulation tasks within ETL pipelines.
- Data Quality Assurance: Develop and implement data quality checks to ensure data accuracy and consistency throughout the pipeline.
- Database Management: Interact with relational and NoSQL databases using SQL queries to retrieve, store, and manage data.
- Cloud Integration: Utilize cloud platforms like AWS, Azure, or GCP to build and manage scalable data infrastructure.
- Big Data Processing: Leverage distributed computing frameworks like Apache Spark to process large volumes of data efficiently.
- Data Modeling: Design data models to optimize data storage and retrieval within data warehouses and data lakes.
- Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights.
- Machine Learning & AI libraries integration: Use Machine learning and GenAI libraries to manipulate and map data
- Data Microservices: Develop python based RESTful APIs for data access and manipulation.
Required Skills:
- Programming Languages: Expert proficiency in Python, including libraries like Pandas, NumPy, and potentially Scikit-learn
- SQL: Strong SQL skills to query and manipulate data in relational databases
- Data Warehousing: Understanding of data warehousing concepts and tools (e.g., Redshift, Snowflake)
- Data Engineering Tools: Familiarity with data pipeline orchestration tools (e.g., Apache Airflow)
- Cloud Computing: Knowledge of cloud platforms (AWS, Azure, GCP) and related data services
- Big Data Technologies: Experience with distributed computing frameworks like Apache Spark (preferred)
- Data Modeling: Ability to design efficient data models for data storage and retrieval
- GenAI: Integration with GenAI services
- Data Web Services: Developing Data services similar to Hasura.
Why Join Us:
Opportunity to work with cutting-edge technology in a collaborative and fast-paced environment.
Competitive salary and benefits package.
Work with a team that values innovation, automation, and continuous improvement.
Career growth opportunities in an expanding engineering organization.
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