Senior Data Engineer

9 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Full Time

Job Description

Company Description

Intellekt AI collaborates with companies to gain a deep understanding of their specific industrial landscapes and designs innovative AI solutions that revolutionize their business operations. Our versatile skill set and comprehensive industry knowledge enable us to consistently deliver successful outcomes tailored to unique requirements.


Notable achievements include developing an automated plane parking system for Airports in the US and Canada, developing an AI solution for brain tumor detection and chest X-ray abnormality detection, and creating a profitable ML-based trading strategy for a leading hedge fund.


Role Description

This is a full-time remote role for a Senior Data Engineer. The Senior Data Engineer will be responsible for designing, developing, and maintaining robust data pipelines, modeling data to support business intelligence and analytics needs, executing Extract Transform Load (ETL) processes, and managing data warehousing solutions.


Qualifications

  • Data Engineering, Data Modeling, and Data Warehousing skills
  • 5–9 years total,

    5+ years

    focused on

    data engineering

    for production analytics.
  • Strong

    SQL

    (window functions, joins, aggregates, query plans) and

    Python

    for ETL.
  • Hands-on

    Airflow

    (DAG design, retries, backfills, SLAs) and incremental loads (watermarks/CDC).
  • Proven

    warehouse design

    from OLTP → OLAP (facts/dims, SCD, conformed dimensions).
  • Experience with

    MySQL/PostgreSQL

    and at least one analytical store (e.g., Postgres/Timescale, Redshift, ClickHouse, BigQuery, Snowflake—any).
  • Data quality & governance: tests, schema/migration discipline, lineage/docs.
  • Cloud

    familiarity (preferably

    AWS

    : S3, RDS, IAM, CloudWatch) and containerized dev (

    Docker

    ).
  • Clear communication; comfortable working remote/asynchronous.
  • CDC tooling (Debezium/Stream-based), message queues (Kafka/Kinesis/SQS), and simple

    streaming

    joins/windows.
  • dbt or similar transformation frameworks; semantic layer experience (metrics catalogs).
  • Cost/perf tuning on cloud warehouses; caching strategies for BI/chat workloads.
  • Security & compliance basics: PII handling, encryption, audit logs, access reviews.

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