Technical Lead

7 days ago

Pune, Maharashtra, India NCSI Technologies Full time ₹ 1,20,000 - ₹ 3,00,000 per year

1 Designing and implementing data ingestion pipelines from multiple sources using Azure Databricks

2 Ensure data pipelines run smoothly and efficiently

3 Developing scalable and re-usable frameworks for ingesting of data sets

4 Integrating the end-to-end data pipeline - to take data from source systems to target data repositories ensuring the quality and consistency of data is maintained at all times

5 Working with event based / streaming technologies to ingest and process data

6 Working with other members of the project team to support delivery of additional project components (API interfaces, Search)

7 Evaluating the performance and applicability of multiple tools against customer requirements

8 Technically competent in Cloud and Databricks to provide technical advice to the team and to be involved in issue resolution

9 Provide on-call support and afterhours/weekend support as needed

10 Fulfill Service Requests related to Data Analytics platform

11 Lead and drive optimization and continuous improvement initiatives

12 Play gate-keeping role and conduct technical review of the changes as part of release management

13 Understand various data security standards and adhere to the required data security controls in the platform

14 Lead the design, development, and deployment of advanced data pipelines and analytical workflows on the Databricks Lakehouse platform.

15 Collaborate with data scientists, engineers, and business stakeholders to build and scale end-to-end data solutions.

16 Own architectural decisions and ensure adherence to data governance, security, and compliance requirements.

17 Mentor a team of data engineers, providing technical guidance and career development.

Implement CI/CD practices for data engineering pipelines using tools like Azure DevOps, GitHub Actions, or Jenkins.

Roles and Responsibilities

Essential for this role:

Education and Qualifications:

• Bachelor's degree in IT, Computer Science, Software Engineering, Business Analytics or equivalent.

• Minimum seven plus years of experience in data analytics field

• Experience with Azure/AWS Databricks

• Experience in building and optimizing data pipelines, architectures and data sets

• Excellent experience in Scala or Python, PySpark and SQL

• Ability to troubleshoot and optimize complex queries on the Spark platform

• Knowledgeable on structured and unstructured data design / modelling, data access and data storage techniques

• Expertise in designing and deploying data applications on cloud solutions, such as Azure or AWS

• Hands on experience in performance tuning and optimizing code running in Databricks environment

• Demonstrated analytical and problem-solving skills particularly those that apply to a big data environment

Technical / Professional Skills :


• Excellent communication skills / should interact directly with the customer

• Azure/AWS Databricks

• Python / Scala / Spark / PySpark

• HIVE / HBase / Impala / Parquet

• Sqoop, Kafka, Flume

• Very Strong SQL and RDBMS

• Airflow

• Jenkins / Bamboo

• Github / Bitbucket

• Nexus

• Knowledge on Delta Live Tables (DLT) will be an added advantage

Good to have:

• Relevant accredited certifications for Azure, AWS, Cloud Engineering, and/or Databricks

• Data Engineering expertise in Big Data Management using Cloudera, Python, Hive, Scala, Data Warehouse, Data Lake, AWS, Azure

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