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Lead GCP Data Engineer
3 weeks ago
Work Location
– Pune (Hybrid)Experience
- 8 to 10 Years
Must have skills:8+ years
of proven experience as a Lead in
Big Data Engineering .Mandatory Technical Proficiency - Hands-on experience with
Python ,
PySpark ,
Google Cloud Full Stack ,
SQL ,
DevOps ,
Databricks ,
DBT & Terraform .Experience with Google Cloud Services such as Streaming
+Batch, Cloud Storage, Cloud Dataflow, Data Proc, Big Query & Big TableProven real-time exposure and use of contemporary data mining, cloud computing, and data
management ecosystems like
Google Cloud, Hadoop, HDFS, and Spark.Proficient in Data Modelling that can represent complex data structures while ensuring accuracy, consistency, and efficiency;
data warehousing , and
ETL processes .Ability to perform system analysis and assessment of existing Systems Design and operating methodologies leveraging in-depth knowledge of big data technologies and ecosystems.Experience with
GitHub, Anaplan, Looker & Power BI,Excellent problem-solving skills and the ability to address complex technical challenges.Strong communication and leadership skills.
Good to have:Experience with Apigee, Apollo GraphQL.Experience with Quality Assurance,
Agile , Documentation & Presentation.Experience with serverless
Data warehousing concepts,Knowledge of
Snowflake ,
ML - Machine Learning, Gen AI (LLMs),
Marketing activation.
Role & Responsibilities:Accountable for overall technical implementations and management of respective engineering PODLiaise with Foundry on solutions design; Agile Project Manager on planning & estimation; Engineers on task assignment; Business stakeholders on prioritizationStreamline workflows and orchestrate
Data pipelines .Automate deployments and facilitate
MTQ/MTP
through
CI-CD/DevOpsConduct code reviews, automate regression tests, and facilitate data reloads.Participate in requirements gathering and architectural discussions.Responsible for the Overall Quality of Engineering builds and Architecture.Technical Leadership: Lead creation of technical design/specifications and provide technical leadership and guidance to development teams, promoting best practices. Provide expertise in Master Data Management, Reference Data Management,
Data Quality ,
Meta Data Management , and
Data Governance
in General.Programming Hands on: Develop and maintain software components using
Python ,
PySpark , and
GCP
services
to process and analyze large datasets efficiently. Build data pipelines and perform data transformations.Enforce consistent standards and quality through end-to-end review of all artifacts
(incl.
BRD, HLD, LLD, Data Models, STTMs, UI-UX, NFRs, Code, Test, PBI architecture design)POC and Pilot of new reusable frameworks, tools & technologies.Evaluate the newest technologies for optimization opportunities and future enhancement needs like self-serve and ad hoc reporting. Implement necessary infrastructure for optimal and efficient
ETL
from disparate data.Performance Optimization : Identify and address performance bottlenecks, ensuring the system meets required throughput and latency targets.Security and Compliance : Ensure that data solutions adhere to security and compliance standards, implementing necessary controls and encryption mechanisms.Scalability : Architect scalable and highly available data solutions, considering both batch and real-time processing.Documentation : Create and maintain comprehensive technical documentation to support the development and maintenance of data solutions
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