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Role Summary
We are looking for a hands-on Senior Data Engineer with 8+ years of experience to join our platform
implementation team. You will play a central role in building a production-grade healthcare data
platform using Snowflake on AWS, ingesting data from on-premise systems, and enabling
downstream analytics and reporting capabilities.
The platform is being evaluated across two architectural patterns: a Snowflake-centric model, where
Snowflake serves as the primary engine for storage, compute, and governance, and a Data
Lakehouse with BYOS (Bring Your Own Storage) model, where AWS S3 forms the storage backbone
with Snowflake integrated on top for processing and querying. You will contribute to architecture
decisions, own end-to-end pipeline development, and ensure the platform meets healthcare-grade
security and governance requirements.
Key Responsibilities
Lead the technical design and hands-on development of scalable, high-performance data
platforms and solutions, providing technical guidance and direction to the engineering team.
Contribute to defining and implementing data architecture principles, ensuring alignment
with enterprise data strategy.
Implement enterprise level data engineering standards, frameworks, and patterns while
ensuring adherence to security, compliance, and performance best practices.
Lead the development of highly efficient, fault tolerant, and cost optimized data pipelines
across Azure, Snowflake, and AWS.
Design and build scalable data ingestion pipelines supporting both batch and near real time
patterns, leveraging cloud native services across Azure, Snowflake, and AWS.
Apply layered data modelling patterns (e.g., medallion architecture) to structure and govern
data platforms, contributing to architecture evaluation across Data Lakehouse models.
Implement data governance capabilities including role based access control, dynamic data
masking, row level security, and column level policies to protect sensitive data assets.
Provide technical guidance and hands on expertise to engineering team, ensuring best in
class data product development, and mentoring junior engineers.
Collaborate with security teams to ensure data engineering solutions comply with security
and regulatory requirements while implementing data governance best practices.
Engage with Product Owners, Data Architects, and Engineering teams to deliver scalable and
reliable data solutions through agile sprint cycles.
Required Skills
Hands on experience with Snowflake architecture: virtual warehouses, clustering, time
travel, data sharing, and zero copy cloning.
Proficiency in Snowpark (Python/Java) for advanced transformations and Snowflake Streams
& Tasks for CDC and incremental loading.
Experience with Snowflake governance features: RBAC, data masking, secure views, and
object tagging.
Practical experience with AWS data services: S3, Glue, DMS, Lambda, Kinesis, Step Functions,
and IAM.
Understanding of BYOS/external table patterns, S3 based data lake design, and Snowflake
AWS integration via Storage Integrations and external stages.
Strong SQL skills with experience in complex transformations, window functions, and query
optimisation.
Experience building ELT/ETL pipelines and implementing Medallion or equivalent layered
data architectures.
Proficiency with dbt for modular, testable, and version-controlled transformation
development.
Familiarity with Apache Airflow or equivalent orchestration tools for complex pipeline
scheduling.
Experience working with on-premise-to-cloud data migration projects.
Strong understanding of data security, access control, and compliance requirements.
Proficiency with Git and CI/CD practices for data engineering workflows.
Qualifications
Bachelors Degree in Computer Science, Software Engineering, or equivalent professional
experience or MCA.
4-6 years of relevant experience in Data Engineering, building and delivering enterprise-scale
data solutions, with a strong preference for cloud expertise in Snowflake, Azure, and AWS.
Kindly reply to this email without changing the subject line with an updated copy of your resume along with the following details.
Current CTC:
Expected CTC:
Notice Period:
AI Screening
As part of our evaluation process, an initial AI screening round invite will be shared with you shortly. We request you to complete this assessment at the earliest, as it plays a crucial role in strengthening your profile and helps us process your candidature more effectively with the client.
Thanks & regards,
Team Finjo
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Job ID: 149535863
Skills:
Azure, Python, AWS, ETL ELT tools, Snowflake SQL
Skills:
MongoDB, Pig, Sql, Java, Storm, Postgres, Hadoop, Kafka, Spark Streaming, AWS, Redis, Hive, Cassandra, Python, Nosql, Gcp, Scala, Elasticsearch, Couchdb, Spark, Apache Druid, Flink, Apache Pinot
Skills:
Java, Sparql, SAP BTP, Prometheus, Kafka, Flux, Grafana, ELT, Typescript, Rdf, Gcp, Helm, Azure, Python, Kubernetes, AWS, Etl, K8s Operators, owl, Crossplane, kubectl, ArgoCD
Skills:
data engineering , Data Architecture, Data Governance, Data Modeling, Data Integration, Sql, Etl, ELT, data pipelines, ontology development, Palantir Foundry
Skills:
Azure Synapse, Sql, Databricks, Azure Data Factory, Pyspark, Azure DevOps, Azure ML, Vertex AI, GCP Cloud Composer, GCP Cloud Run, GCP DLP, GCP BigQuery, FiveTran
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