3+ Data archiving Jobs in India

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.

MANDATORY:

• Super Quality Data Architect, Data Engineering Manager / Director Profile
• Must have 12+ YOE in Data Engineering roles, with at least 2+ years in a Leadership role
• Must have 7+ YOE in hands-on Tech development with Java (Highly preferred) or Python, Node.JS, GoLang
• Must have strong experience in large data technologies, tools like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto etc.
• Strong expertise in HLD and LLD, to design scalable, maintainable data architectures.
• Must have managed a team of at least 5+ Data Engineers (Read Leadership role in CV)
• Product Companies (Prefers high-scale, data-heavy companies)

PREFERRED:

• Must be from Tier - 1 Colleges, preferred IIT
• Candidates must have spent a minimum 3 yrs in each company.
• Must have recent 4+ YOE with high-growth Product startups, and should have implemented Data Engineering systems from an early stage in the Company

ROLES & RESPONSIBILITIES:

• Lead and mentor a team of data engineers, ensuring high performance and career growth.
• Architect and optimize scalable data infrastructure, ensuring high availability and reliability.
• Drive the development and implementation of data governance frameworks and best practices.
• Work closely with cross-functional teams to define and execute a data roadmap.
• Optimize data processing workflows for performance and cost efficiency.
• Ensure data security, compliance, and quality across all data platforms.
• Foster a culture of innovation and technical excellence within the data team.

IDEAL CANDIDATE:

• 10+ years of experience in software/data engineering, with at least 3+ years in a leadership role.
• Expertise in backend development with programming languages such as Java, PHP, Python, Node.JS, GoLang, JavaScript, HTML, and CSS.
• Proficiency in SQL, Python, and Scala for data processing and analytics.
• Strong understanding of cloud platforms (AWS, GCP, or Azure) and their data services.
• Strong foundation and expertise in HLD and LLD, as well as design patterns, preferably using Spring Boot or Google Guice
• Experience in big data technologies such as Spark, Hadoop, Kafka, and distributed computing frameworks.
• Hands-on experience with data warehousing solutions such as Snowflake, Redshift, or BigQuery
• Deep knowledge of data governance, security, and compliance (GDPR, SOC2, etc.).
• Experience in NoSQL databases like Redis, Cassandra, MongoDB, and TiDB.
• Familiarity with automation and DevOps tools like Jenkins, Ansible, Docker, Kubernetes, Chef, Grafana, and ELK.
• Proven ability to drive technical strategy and align it with business objectives.
• Strong leadership, communication, and stakeholder management skills.

PREFERRED QUALIFICATIONS:

• Experience in machine learning infrastructure or MLOps is a plus.
• Exposure to real-time data processing and analytics.
• Interest in data structures, algorithm analysis and design, multicore programming, and scalable architecture.
• Prior experience in a SaaS or high-growth tech company.

Job Description – Developer (ETL + Database)

 Develop, document & Support ETL mappings, Database structures & BI reports.

 Perform unit testing of developments done by him/her.

 Participate in UAT process and ensure quick resolution of any UAT issue.

 Manage different environments and be responsible for proper deployment of code in all client

environments.

 Prepare release documents.

 Prepare and Maintain project documents as advised by Team Leads.

Skill-sets:

 3+ years of Hands on experience on ETL Pentaho Spoon Talend & MS SQL Server, Oracle & SYBASE Database tools.

 Ability to write complex SQL and database procedures.

 Good knowledge and understanding regarding Data warehouse Concepts, ETL Concepts, ETL

Loading Strategies, Data archiving, Data Reconciliation, ETL error handling etc.

 Problem Solving.

 Good communication skills – written and verbal.

 Self-motivated, team player, action and result oriented.

 Ability to successfully work under tight project schedule