Senior Analytics Engg_AWS + BI Tools_Bangalore_Early joiners_10+ years

HCL Technologies
Posted on
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Experience
9 - 14 yrs
Salary (CTC)
2,000,000 - 3,500,000
Job Location
Bengaluru, India
Vacancy
2
Designation
Senior Analytics Engineer
Job Type
ONSITE

Job Description

HI,


Greetings for the day !!!


We at HCL are looking Data Analytics Engineers with exp in AWS, Python, CI CD, SQL, Power Bi or Tableau


Location: Only Bangalore


Looking for Immediate joiners


If interested reach us on srikanth.domala@hcltech.com

Provide us the details below:

Total years of exp:

Exp in AWS:

Exp in Python/Pyspark:

Exp in SQL:

Exp in Data Visualization tools:


Current CTC:

Expected CTC:

Notice Period:

Current location:

Preferred location:


JD as below:


Key responsibilities

  • Modelling and ELT: design star schemas and domain marts; implement tests

(schema, data, freshness), documentation, and incremental strategies.

  • Metrics governance: Define and version business metrics (owners,

contracts, change control); implement semantic layer (dbt Semantic

Layer/MetricFlow) and ensure consistency across BI.

  • BI delivery: Support building BI datasets and dashboards; implement

RLS/column level security; optimise SPICE, query performance, and UX.

  • Quality and reliability: Add DQ checks in pipelines; monitor freshness

and accuracy; partner with Core Data Engineer on upstream contracts and SLAs.

  • CI/CD and workflow: Git driven development, PR reviews, environment

promotion; automate model validation and BI artefact deployment.

  • Performance tuning: Redshift sort/dist keys, WLM/concurrency scaling;

Athena partitioning and file formats for efficient queries.

  • Enablement: Translate requirements, document definitions, run training,

and maintain a catalogue of metrics/datasets in Glue Catalog.

Outcomes (first 6090 days)

  • Ship a governed KPI suite (metric catalogue + dbt models) and at least

two business critical dashboards with RLS.

  • Establish CI/CD for analytics repo with automated tests and promotions;

reduce dashboard query times via model and dataset tuning.

  • Publish clear documentation for metrics, dimensions, lineage, and

ownership.

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