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Job Overview:
We are seeking an experienced AWS Data Engineer to join our growing data team. The ideal candidate will have hands-on experience with AWS Glue, Redshift, PySpark, and other AWS services to build robust, scalable data pipelines. This role is perfect for someone passionate about data engineering, automation, and cloud-native development.
Key Responsibilities:
- Design, build, and maintain scalable and efficient ETL pipelines using AWS Glue, PySpark, and related tools.
- Integrate data from diverse sources and ensure its quality, consistency, and reliability.
- Work with large datasets in structured and semi-structured formats across cloud-based data lakes and warehouses.
- Optimize and maintain data infrastructure, including Amazon Redshift, for high performance.
- Collaborate with data analysts, data scientists, and product teams to understand data requirements and deliver solutions.
- Automate data validation, transformation, and loading processes to support real-time and batch data processing.
- Monitor and troubleshoot data pipeline issues and ensure smooth operations in production environments.
Required Skills:
- 5 to 7 years of hands-on experience in data engineering roles.
- Strong proficiency in Python and PySpark for data transformation and scripting.
- Deep understanding and practical experience with AWS Glue, AWS Redshift, S3, and other AWS data services.
- Solid understanding of SQL and database optimization techniques.
- Experience working with large-scale data pipelines and high-volume data environments.
- Good knowledge of data modeling, warehousing, and performance tuning.
Preferred/Good to Have:
- Experience with workflow orchestration tools like Airflow or Step Functions.
- Familiarity with CI/CD for data pipelines.
- Knowledge of data governance and security best practices on AWS.
Job Title : Tech Lead - Data Engineering (AWS, 7+ Years)
Location : Gurugram
Employment Type : Full-Time
Job Summary :
Seeking a Tech Lead - Data Engineering with expertise in AWS to design, build, and optimize scalable data pipelines and data architectures. The ideal candidate will have experience in ETL/ELT, data warehousing, and big data technologies.
Key Responsibilities :
- Build and optimize data pipelines using AWS (Glue, EMR, Redshift, S3, etc.).
- Maintain data lakes & warehouses for analytics.
- Ensure data integrity through quality checks.
- Collaborate with data scientists & engineers to deliver solutions.
Qualifications :
- 7+ Years in Data Engineering.
- Expertise in AWS services, SQL, Python, Spark, Kafka.
- Experience with CI/CD, DevOps practices.
- Strong problem-solving skills.
Preferred Skills :
- Experience with Snowflake, Databricks.
- Knowledge of BI tools (Tableau, Power BI).
- Healthcare/Insurance domain experience is a plus.

at Altimetrik
-Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight.
-Experience in developing lambda functions with AWS Lambda.
-
Expertise with Spark/PySpark
– Candidate should be hands on with PySpark code and should be able to do transformations with Spark
-Should be able to code in Python and Scala.
-
Snowflake experience will be a plus

Urgent Openings with one of our client
Experience : 3 to 7 Years
Number of Positions : 20
Job Location : Hyderabad
Notice : 30 Days
1. Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
2. Experience in developing lambda functions with AWS Lambda
3. Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
4. Should be able to code in Python and Scala.
5. Snowflake experience will be a plus
Hadoop and Hive requirements as good to have or understanding of is enough.