2+ Data masking Jobs in India

JOB DETAILS:

* Job Title: Associate III - Data Engineering

* Industry: Global digital transformation solutions provide

* Salary: Best in Industry

* Experience: 4-6 years

* Location: Trivandrum, Kochi

Job Description

Job Title:

Data Services Engineer – AWS & Snowflake

Job Summary:

As a Data Services Engineer, you will be responsible for designing, developing, and maintaining robust data solutions using AWS cloud services and Snowflake.

You will work closely with cross-functional teams to ensure data is accessible, secure, and optimized for performance.

Your role will involve implementing scalable data pipelines, managing data integration, and supporting analytics initiatives.

Responsibilities:

• Design and implement scalable and secure data pipelines on AWS and Snowflake (Star/Snowflake schema)

• Optimize query performance using clustering keys, materialized views, and caching

• Develop and maintain Snowflake data warehouses and data marts.

• Build and maintain ETL/ELT workflows using Snowflake-native features (Snowpipe, Streams, Tasks).

• Integrate Snowflake with cloud platforms (AWS, Azure, GCP) and third-party tools (Airflow, dbt, Informatica)

• Utilize Snowpark and Python/Java for complex transformations

• Implement RBAC, data masking, and row-level security.

• Optimize data storage and retrieval for performance and cost-efficiency.

• Collaborate with stakeholders to gather data requirements and deliver solutions.

• Ensure data quality, governance, and compliance with industry standards.

• Monitor, troubleshoot, and resolve data pipeline and performance issues.

• Document data architecture, processes, and best practices.

• Support data migration and integration from various sources.

Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.

• 3 to 4 years of hands-on experience in data engineering or data services.

• Proven experience with AWS data services (e.g., S3, Glue, Redshift, Lambda).

• Strong expertise in Snowflake architecture, development, and optimization.

• Proficiency in SQL and Python for data manipulation and scripting.

• Solid understanding of ETL/ELT processes and data modeling.

• Experience with data integration tools and orchestration frameworks.

• Excellent analytical, problem-solving, and communication skills.

Preferred Skills:

• AWS Glue, AWS Lambda, Amazon Redshift

• Snowflake Data Warehouse

• SQL & Python

Skills: Aws Lambda, AWS Glue, Amazon Redshift, Snowflake Data Warehouse

Must-Haves

AWS data services (4-6 years), Snowflake architecture (4-6 years), SQL (proficient), Python (proficient), ETL/ELT processes (solid understanding)

Skills: AWS, AWS lambda, Snowflake, Data engineering, Snowpipe, Data integration tools, orchestration framework

Relevant 4 - 6 Years

python is mandatory

******

Notice period - 0 to 15 days only (Feb joiners’ profiles only)

Location: Kochi

F2F Interview 7th Feb

ROLES AND RESPONSIBILITIES:

You will be responsible for architecting, implementing, and optimizing Dremio-based data Lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.

• Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
• Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
• Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
• Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
• Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
• Support self-service analytics by enabling governed data products and semantic layers.
• Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
• Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.

IDEAL CANDIDATE:

• Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
• 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
• Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
• Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
• Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
• Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
• Excellent problem-solving, documentation, and stakeholder communication skills.

PREFERRED:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
• Exposure to Snowflake, Databricks, or BigQuery environments.
• Experience in high-tech, manufacturing, or enterprise data modernization programs.