Tech Lead, Data Engineer, Data Analyst

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• Design and implement Snowflake schemas (star, snowflake, data vault) optimized with micro-partitioning, clustering keys, materialized views, and search optimization services.
• Build real-time and batch ingestion pipelines into Snowflake using Snowpipe, Kafka Connect, Fivetran, Matillion, Informatica, or dbt.
• Automate incremental data processing with Streams & Tasks to support CDC (Change Data Capture).
• Use Zero-Copy Cloning for environment management, testing, and sandboxing.
• Apply Time Travel and Fail-safe features for data recovery and auditing.
• Develop data transformation logic in Snowpark for Python/SQL/Scala to push compute directly into Snowflake.
• Design integrations with cloud storage (S3, Azure ADLS, GCS) for staging and external tables.
• Implement data sharing and data marketplace solutions via Snowflake Secure Data Sharing and Snowflake Marketplace.
• Enable semi-structured data handling (JSON, Avro, Parquet, ORC, XML) using VARIANT columns and lateral flattening.
• Integrate Snowflake with BI tools (Power BI, Tableau) via live connections and semantic layers.
• Implement RBAC (Role-Based Access Control), Row Access Policies, and Dynamic Data Masking for data security.
• Optimize compute usage with multi-cluster warehouses, resource monitors, and query performance tuning.
• Manage cost optimization strategies (warehouse auto-suspend, query profiling, storage/compute separation).
• Integrate with data catalog & governance platforms (Collibra, Alation, Informatica CDGC) using Snowflake metadata and APIs.
• Work with domain teams to deliver data products leveraging Snowflake’s data mesh-friendly features.
• Collaborate with architects to design a Snowflake-centric data fabric integrated with ETL/ELT and API layers.
• Support CI/CD automation for Snowflake code deployment using Git Hub Actions, Azure Dev Ops, or dbt Cloud.

Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.

• 10+ years of data engineering experience, with 5+ years in Snowflake Data Cloud.
• Expertise in SQL optimization and Snowflake performance tuning.
• Hands‑on with Snowpipe, Streams & Tasks, Snowpark, Zero‑Copy Cloning, and Secure Data Sharing.
• Proficiency in Python, Scala, or Java for Snowpark development.
• Experience integrating with cloud platforms like AWS.
• Exposure to ETL/ELT tools (Informatica, Matillion, Fivetran).
• Familiarity with CI/CD, Git, Dev Ops practices for data operations.
• Preferred
  
  Certifications:

• Snowflake-native feature design and implementation (Snowpark, Streams, Time Travel, Secure Data Sharing)
• Semi‑structured data handling (VARIANT, JSON, Avro, Parquet)
• Advanced SQL and performance tuning
• Data governance (RBAC, masking, lineage, catalogs)
• Cloud data platform integrations (AWS S3, Azure ADLS, GCP GCS)
• BI and analytics tool integration
• Cost optimization and warehouse orchestration

The pay range for this role is $120k - $130k per annum including any bonuses or variable pay. Tech Mahindra also offers benefits like medical, vision, dental, life, disability insurance and paid time off (including holidays, parental leave, and sick leave, as required by law). Ask our recruiters for more details on our Benefits package. The exact offer terms will depend on the skill level, educational qualifications, experience, and location of the candidate.

Tech Mahindra is an Equal Employment Opportunity employer. We promote and support a diverse workforce at all levels of the company. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, age, national origin or disability. All applicants will be evaluated solely on the basis of their ability, competence, and performance of the essential functions of their positions with or without reasonable accommodations.

Reasonable accommodations also are available in the hiring process for applicants with disabilities. Candidates can request a reasonable accommodation by contacting the company ADA Coordinator at ADA_A .